{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "960ceacb-3c3f-484c-95b9-172bd009b1a4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a generic code for drawing a state's Home Districts for neutral map estimation\n",
      "In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\n"
     ]
    }
   ],
   "source": [
    "#  This is a modification to vanillaHD-MO to build a VRA in St Louis\n",
    "print(\"This is a generic code for drawing a state's Home Districts for neutral map estimation\") #Jan'24\n",
    "print(\"In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\")\n",
    "import shapely\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "from shapely.ops import nearest_points, transform\n",
    "from shapely.affinity import translate, scale\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "from scipy.optimize import minimize, minimize_scalar\n",
    "import math\n",
    "import time\n",
    "import ast\n",
    "# from HDmethods import *   #I want to implement this, but my HDmethods require shapely functions\n",
    "# see https://stackoverflow.com/questions/66877728/proper-way-to-use-import-when-calling-external-function for a future workaround\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "id": "2ab4a3d5-f4e7-4aec-b81c-0e786cd35b57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def getWeightedAvgAndSD(LIST, WEIGHTS):  #from IN\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def squish(shapeList, cutLINE, farLINE, newFarLINE):\n",
    "    \"\"\"\n",
    "    This method compresses a list of shapes lying between the cutLINE and the farLINE)\n",
    "    such that the Polygons now lie between the cutLINE and the newFarLINE, which is closer to the cutLINE\n",
    "    Used to compress state outcroppings into a more compact state representation.\n",
    "     (I tried doing this point by point (see #'s), but this overdistorted geometries.)\n",
    "      (#This was a manual alternative to shapely.affinity.scale and .translate operations)\n",
    "       So instead, we run this AFTER established untransformed map topology, and \n",
    "        we simply scale and translate each unit.  This loses true connectivity.\n",
    "        Scaling is all lengths scale by compression of distance\n",
    "    The cut, far, and newFar LineString segments are preferably parallel\n",
    "    The method returns the modified shapes of all pollys\n",
    "    \"\"\"\n",
    "    if cutLINE.intersects(farLINE) or cutLINE.intersects(newFarLINE):\n",
    "        print(\"cutLine,farLine, newFarLine were\",cutLINE, farLINE, newFarLINE)\n",
    "        raise Exception(\"ERROR: the proposed cutLine intersects the current or proposed far line\")\n",
    "    newPollys = list()\n",
    "    for polly in shapeList:\n",
    "        pollyCP = polly.centroid\n",
    "        cutPt =     nearest_points(cutLINE,   pollyCP)[0]\n",
    "        farPt =     nearest_points(farLINE,   pollyCP)[0]\n",
    "        newFarPt =  nearest_points(newFarLINE,pollyCP)[0]\n",
    "        curr_cutX, curr_cutY =            pollyCP.x - cutPt.x, pollyCP.y -  cutPt.y\n",
    "        currFar_CutX , currFar_CutY  =    farPt.x - cutPt.x, farPt.y   -  cutPt.y\n",
    "        new_currFarX, new_currFarY =      newFarPt.x - farPt.x, newFarPt.y - farPt.y\n",
    "        newFar_CutX,  newFar_CutY =       newFarPt.x - cutPt.x, newFarPt.y   -  cutPt.y\n",
    "        distanceRatio = newFarPt.distance(cutPt)/farPt.distance(cutPt) #scale area ^length^2\n",
    "        XOFF,YOFF = 0., 0.\n",
    "        XFACT, YFACT = 1., 1.  #default = no stretch\n",
    "        # basic equation: (new-cut)/(curr-cut) = (newFar-cut)/(currFar - cut)\n",
    "        #  or: (new-curr)  = (curr-cut)*(newFar-currFar)/(currFar - cut)   # -1 to both sides\n",
    "        if currFar_CutX != 0:\n",
    "            XOFF =  curr_cutX * new_currFarX / currFar_CutX\n",
    "            XFACT =              newFar_CutX / currFar_CutX\n",
    "        if currFar_CutY != 0:\n",
    "            YOFF =  curr_cutY * new_currFarY / currFar_CutY\n",
    "            YFACT =              newFar_CutY / currFar_CutY\n",
    "        newPolly = translate(polly,xoff=XOFF,yoff=YOFF)\n",
    "        newPolly = scale(newPolly, xfact=XFACT, yfact=YFACT, origin='centroid')\n",
    "        newPollys.append( newPolly )       \n",
    "    return newPollys\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "#  The below four methods are TO SNAP to HD SHAPES without any solving / iteration\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    The optional xScale parameter is the ratio of longitude to latitude lengths scales (<<1 for far from equator)\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def buildPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a 4-tri polygon from four HD wedges emanating from the centerpoint\n",
    "    Pt = [Point(0,0)]*12                      #xScale has same meaning as in buildWedge\n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW]  #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ]  \n",
    "        Pt[nW*2] =   Point(CP.x + RADII[nW]/XSCALE*math.cos(ccwAngle), CP.y + RADII[nW]*math.sin(ccwAngle) )\n",
    "        Pt[nW*2+1] = Point(CP.x + RADII[nW]/XSCALE*math.cos( cwAngle), CP.y + RADII[nW]*math.sin( cwAngle) )        \n",
    "    POLLY = Polygon([Pt[0],Pt[1],Pt[2],Pt[3],Pt[4],Pt[5],Pt[6],Pt[7] ])\n",
    "    return POLLY\n",
    "\n",
    "def buildArcPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a fuller polygon from four HD wedges emanating from the centerpoint\n",
    "    twoPi = 2. * 3.1415926   #xScale has same meaning as in buildWedge\n",
    "    POINTS = list()                   \n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW] % twoPi                 #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ] % twoPi \n",
    "        midAngle = [0.75*ccwAngle + 0.25*cwAngle , 0.25*ccwAngle + 0.75*cwAngle ]  #avoid s sampling cone center for wide angles\n",
    "        if abs (ccwAngle - cwAngle) > 3.1415926 :  #angles straddle angle=0\n",
    "            midAngle = [0.75*(ccwAngle - twoPi) + 0.25*cwAngle , 0.25*(ccwAngle -twoPi) + 0.75*cwAngle ]\n",
    "        angList = [ccwAngle] + midAngle + [cwAngle]\n",
    "        for ang in angList:\n",
    "            POINTS.append(Point(CP.x + RADII[nW]/XSCALE*math.cos(ang), CP.y + RADII[nW]*math.sin(ang) ) )\n",
    "                          \n",
    "    POLLY = Polygon(POINTS)\n",
    "    return POLLY\n",
    "\n",
    "def getPolyPop(POLLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points contained by a polygon\n",
    "    WPOP, WLIST = 0., list()\n",
    "    for tt in CANDIDATELIST:\n",
    "        if POLLY.contains(TRACTCP[tt]):\n",
    "            WPOP += TRACTPOP[tt]\n",
    "            WLIST.append(tt)\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonCPP(POLLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county in getPolyPop\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if POLLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonHCunits(POLLY, HC, UNITLIST, UNITCP, UNITPOP, ALLFUSEDCOUNTIES, AREAFRAC, COUNTYGEOM, \n",
    "                  NEIGHBORCOUNTYLIST, COUNTYUNITLIST):\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"unit counties\" are added as whole units if a sufficient area fraction is captured.  For non-unitCs, we probe each component vtd / tract\n",
    "    \"\"\"\n",
    "    UPOP, ULIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county before we called this method\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        #1/9/24 - DO WE NEED TO MODIFY THE ORDER BELOW TO AVOID CREATING HOLES AND ENCLAVES ??  #\n",
    "        \n",
    "        for c in latestClist:\n",
    "            for cc in list( set(NEIGHBORCOUNTYLIST[c]).difference(set(ALLFUSEDCOUNTIES)) ):\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        if cc+0.5 in UNITLIST:\n",
    "                            if POLLY.intersection(COUNTYGEOM[cc]).area >=  AREAFRAC[cc] * COUNTYGEOM[cc].area :\n",
    "                                intersectedClist.append(cc)   #for unit counties, intersections count only if they capture sufficient area\n",
    "                                newClist.append(cc)\n",
    "                                UPOP += UNITPOP[UNITLIST.index(cc+0.5)]\n",
    "                                ULIST.append( UNITLIST.index(cc+0.5) )\n",
    "                        else:                           \n",
    "                            intersectedClist.append(cc)\n",
    "                            newClist.append(cc)\n",
    "                            if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                                unitsToAdd = COUNTYUNITLIST[cc]\n",
    "                                UPOP += np.sum(  [ UNITPOP[uu] for uu in unitsToAdd ]  )\n",
    "                                ULIST += unitsToAdd\n",
    "                            else:\n",
    "                                for uu in COUNTYUNITLIST[cc]:\n",
    "                                    if POLLY.contains(UNITCP[uu]):\n",
    "                                        UPOP += UNITPOP[uu]\n",
    "                                        ULIST.append(uu)\n",
    "        latestClist = newClist.copy()\n",
    "        \n",
    "    return UPOP, ULIST\n",
    "\n",
    "def clusterSwell(CP_, CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, borderUnits, TGTPOP):\n",
    "    \"\"\"\n",
    "    This method grows a Home District by \"swelling\" from a corner county cluster.  First, we add the full cluster,\n",
    "     then we add closest neighbor units to the home district centerpoint CP_ until we reach the TGTPOP\n",
    "     new for MN 4/7/24 - don't enforce contiguity here -- too slow -- fix in cleanup stage instead\n",
    "     \"\"\"\n",
    "    hd_CCBdist = [CP_.distance(geo) for geo in CCBgeom]\n",
    "    CCBno = hd_CCBdist.index(np.min(hd_CCBdist))  #ID's the closest cluster to this HD center.  Should contain the HD, but rarely will not\n",
    "    unitNo = allUnits.index(CCBno+0.25)\n",
    "    newList, prevList, addedList, addedPop = [unitNo], [unitNo], [unitNo], unitPop[unitNo]  #seed with the cluster pop and unit\n",
    "    while addedPop < 0.99 * TGTPOP and len(newList) > 0:\n",
    "        tryList = getAdjoiners(addedList,unitNbrs)\n",
    "        tryDist = [ CP_.distance(unitCP[UU]) for UU in tryList ]\n",
    "        idx = np.argsort(tryDist)\n",
    "        idxNo, newList = 0, list()\n",
    "        haveNotAdded = True\n",
    "        while idxNo < len(tryList) and haveNotAdded:\n",
    "            UU = tryList[idx[idxNo]]\n",
    "            if unitPop[UU] + addedPop < 1.01 * TGTPOP :  #and wontEnclave(UU, addedList, unitNbrs, borderUnits) :  #we'll post-fix contig'y\n",
    "                newList.append(UU)\n",
    "                addedList.append(UU)\n",
    "                addedPop += unitPop[UU]\n",
    "                haveNotAdded = False\n",
    "            idxNo +=1\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    return addedPop, addedList\n",
    "            \n",
    "def getFakeHC(HDPOLLY, HC, CCBlist, countyGeom, MAP) :\n",
    "    \"\"\"\n",
    "    This method is for setting a fake home county for counties in corner clusters, so that county neighbors can be found budding from the \"home county\"\n",
    "    We pick the county in the cluster closest to the map center and intersecting the HDpoly.  This will be an active county on the cluster boundary   \n",
    "    \"\"\"\n",
    "    MAPcenter = MAP.centroid\n",
    "    for L in CCBlist:\n",
    "        if HC in L:\n",
    "            distList, cList = list(), list()\n",
    "            for C in L:\n",
    "                if HDPOLLY.intersects(countyGeom[C]):\n",
    "                    distList.append(countyGeom[C].distance(MAPcenter))\n",
    "                    cList.append(C)\n",
    "    fakeHC = cList[distList.index(np.min(distList)) ]\n",
    "    return fakeHC\n",
    "\n",
    "def getLongDist(CP1, CP2, xScale = 1.0): #distance between two points with EW distance scaled down by latitude\n",
    "    #LAT = MAP.centroid.y\n",
    "    #xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "    dist = ( xScale*xScale * (CP1.x - CP2.x)*(CP1.x - CP2.x)  +  (CP1.y - CP2.y)*(CP1.y - CP2.y) ) **0.5 \n",
    "    return dist\n",
    "\n",
    "# THESE ARE THE METHODS USED IN SOLVING HD SHAPES\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def getCountyWP(T, WEDGEPOLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points in a wedge excluding a point\n",
    "        WPOP, WLIST = 0., list()\n",
    "        for tt in CANDIDATELIST:\n",
    "            if tt != T and WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                WPOP += TRACTPOP[tt]\n",
    "                WLIST.append(tt)\n",
    "        return WPOP, WLIST\n",
    "\n",
    "def getNonCWP(WEDGEPOLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by an infinite polygonal wedge for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def isIncludedA(STARTa, ENDa, TESTa): #determines if a test angle is between a start and end angle (True)\n",
    "    \"\"\"\n",
    "    The start angle must be less than the end angle when placed on the [0, 2 pi] interval  (ccw convention)\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    STARTa, ENDa, TESTa = STARTa % (2.*pi), ENDa % (2.*pi), TESTa % (2.*pi)  #place on the 2pi interval\n",
    "    isIncludedA = False\n",
    "    if STARTa  > ENDa :  #included angle straddles east\n",
    "        if   TESTa  >= STARTa or TESTa < ENDa :  #near-east between the two\n",
    "            isIncludedA = True\n",
    "    else:\n",
    "        if TESTa >= STARTa and TESTa < ENDa :  #normal case\n",
    "            isIncludedA = True\n",
    "    return isIncludedA\n",
    "\n",
    "def getNonCWP_c(STARTANGL, ENDANGL, HC, TRACTCP,TRACTPOP,COUNTYGEOM,COUNTYPOP,COUNTYTRACTLIST,\n",
    "                                    NEIGHBORCOUNTYLIST, UUDIST, UUANGLE, WEDGEPOLY) :\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a polygonal wedge for counties contiguous with the Home County (no hop-overs),\n",
    "    EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    Unlike its getNonCWP vanilla parent, this one uses angles rather than infinite wedges for units (still wedges for counties)\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if isIncludedA(STARTANGL, ENDANGL, UUANGLE[tt]): #WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getExitAngle(CP,WEDGEPOLY, MAP, A0, A1):\n",
    "    \"\"\"\n",
    "    This code determines the orientation angle from a CenterPoint to the intersection of a wedge with an exterior boundary\n",
    "    If an intersection is not found, we just take the average angle of the wedge start/stop angles A0, A1 as this orientation angle\n",
    "    MAP must be a single polygon for this to work in the revised code (tho could run thru all polygons in MAP if a multipolygon)\n",
    "    \"\"\"\n",
    "    EXITANGLE = 0.5* (A0 + A1) #this will be the angle from the x-axis to the exit beeline\n",
    "    if WEDGEPOLY.intersects(MAP.exterior):\n",
    "        edgeLine = WEDGEPOLY.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "        closePoint = nearest_points(edgeLine,CP)[0]\n",
    "        dx = closePoint.x - CP.x       #this and below lines were indented in original code***\n",
    "        dy = closePoint.y - CP.y\n",
    "        EXITANGLE =  pi/2. * np.sign(dy)  #default in case dx=0\n",
    "        if (dx != 0. ):\n",
    "            EXITANGLE = math.atan(dy/dx) + random.uniform(-0.01,0.01) #add wiggle to avoid exact NESW orientation in gridded states\n",
    "            if dx < 0. :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                EXITANGLE = pi + EXITANGLE\n",
    "    return EXITANGLE # this reorients 0th wedge to face boundary's closest point\n",
    "\n",
    "def getNewAngles(mWP, tWP, ADP, LEVEL_L, MINADJRATIO, MAXANGLE, MAXANGLERATIO, nUNFILLEDWEDGES): \n",
    "    \"\"\"\n",
    "    This method classifies Home Districts based on how their post-reoriented equi-angle max wedge pops stack up vs targets,\n",
    "     then changes wedge angles in some situations to pick up more population along the boundary\n",
    "    If there is one wedge that will fall short of a quarter district pop, then we adjust angles if it is sufficiently short    \n",
    "    (Using \"HD2\" code, the opposite wedge's pop will be constrained as well.)\n",
    "    If there are two opposite-facing constrained wedges, we do not adjust angles\n",
    "    If there are two adjacent constrained wedges, we classify as a corner (no angle change) if the adjacent wedge is sufficiently constrained,\n",
    "      otherwise we treat as a single constrained wedge\n",
    "    If there are three constrained wedges, the angles are unchanged; we use the 4th wedge to pick up all pop\n",
    "    If all four wedges are constrained, there is an error and we raise a flag.\n",
    "    mWP is the quadlist of maxWedgePops we would get by extending each wedge to the MAP boundary\n",
    "    tWP is the quadlist of targetWedgePops\n",
    "    LEVEL_L is the non-dimensional distance to the boundary at which we no longer adjust wedge angles to drive more near-boundary pop\n",
    "    MAXANGLERATIO is the max ratio of the wide angle (facing the boundary) to the normal angle (e.g. 90deg for four wedges) ...\n",
    "    but this is truncated near-boundary to MAXANGLE (e.g. 1.8 pi/2 instead of increasing all the way to 1.9 pi/2)\n",
    "      NOTE THAT this code does not consider nearly-shorted wedges -- those are a separate method called later if all mWP's > tWP's\n",
    "    \"\"\"   \n",
    "    isChange = False   #default; we are NOT changing angles\n",
    "    printDebuggg = False\n",
    "    NWEDGES = len(mWP)\n",
    "    avgWedgeAngle = 2.*math.pi / NWEDGES\n",
    "    minW = mWP.index(np.min(mWP))  #index of the wedge with the lowest max wedge pop\n",
    "    oppW = int( int(minW + NWEDGES/2) % NWEDGES )  #and its opposing wedge\n",
    "    Lstar = ( mWP[minW] / (0.25*ADP) )**0.5  #shortest wedge's nondim'l distance to boundary\n",
    "    \n",
    "    case = \"keep same wedge angles\" #default; no unfillable wedges or all but one are unfillable\n",
    "    if nUNFILLEDWEDGES >= NWEDGES:\n",
    "        raise Exception(\"ERROR! ALL WEDGES ARE CONSTRAINED for tract\",t,\".  IMPOSSIBLE!!\")\n",
    "    if nUNFILLEDWEDGES == 1:\n",
    "        case = \"constrain opp wedge\"\n",
    "        if Lstar >= levelL :\n",
    "            case = \"keep same wedge angles\"  #not close enough to boundary to distort HD shape\n",
    "    if nUNFILLEDWEDGES == 0 or nUNFILLEDWEDGES == NWEDGES - 1:  #far from boundary or with only one wedge w/large pop\n",
    "        case = \"keep same wedge angles\"   \n",
    "    if nUNFILLEDWEDGES == 2:  #must determine if opposite or adjacent           \n",
    "        if mWP[oppW] < tWP[oppW]:  #shorted wedges oppose each other, so ...\n",
    "            case = \"keep same wedge angles\" #...the HD shape will naturally widen to pick up adjacent pop\n",
    "        else:  #we have 2 adjacent (non-opposing) shorted wedges... but how shorted?  ID the adjacent wedge\n",
    "            for nW in range(NWEDGES):\n",
    "                if mWP[nW] < tWP[nW] and nW != minW :\n",
    "                    adjW = nW  #this is the adjacent wedge\n",
    "                    adjRatio = mWP[adjW] / tWP[adjW]\n",
    "            if adjRatio < minAdjRatio:  #we're close to a corner (this adjacentWedge is significantly constrained)\n",
    "                case = \"keep same wedge angles\"\n",
    "                if printDebuggg :\n",
    "                    print(\"Not adjusting wedge angles for tract\",t,\"as 2nd-sparsest wedge\",adjW,\"has pop\",mWP[adjW] )\n",
    "            else:\n",
    "                case = \"constrain opp wedge\"  #we will set the angles and target pops as if the adj wedge were not constrained\n",
    "    \n",
    "    if case == \"keep same wedge angles\":\n",
    "        isChange = False\n",
    "        WEDGEANGLE = [avgWedgeAngle for w in range(NWEDGES) ]\n",
    "\n",
    "    if case == \"constrain opp wedge\":  #Here, we modify wedge angles.  MWP's will be recalc'd outside the method\n",
    "        isChange = True  \n",
    "        wideAngle = min(MAXANGLE, avgWedgeAngle*max(  1,( 1.+(MAXANGLERATIO-1.)*(LEVEL_L - Lstar)/(LEVEL_L - 0.) )  ) )\n",
    "        WEDGEANGLE = [(2.*pi - 2. * wideAngle)/ (NWEDGES - 2.) for w in range(NWEDGES) ]  \n",
    "        WEDGEANGLE[minW] = wideAngle\n",
    "        WEDGEANGLE[oppW] = wideAngle\n",
    "    \n",
    "    return isChange, WEDGEANGLE\n",
    "\n",
    "def rebalanceTWPs(MWP, TWP, BARREDLIST=list()):\n",
    "    \"\"\"\n",
    "    This method iteratively increases targetWedgePops to accommodate wedges that have maxWedgePop < targetWedgePop.\n",
    "    The wedgePop gap is distributed equally among wedges that have some capacity and are not BARRED (e.g. an opposite wedge in HD2 method)\n",
    "     (If this pushes some wedges over capacity, this will be fixed in a later run through loop inside this method)\n",
    "    We also flag which wedges \"will fill\" = have sufficient capacity after the rebalancing of the targets to not use the entire maxWedgePoly\n",
    "    \"\"\"\n",
    "    DEBUGrTWP = False\n",
    "    NWEDGES = len(MWP)\n",
    "    unorderedCapacity = [MWP[w] - TWP[w] for w in range(NWEDGES) ]\n",
    "    idx = np.argsort(unorderedCapacity)\n",
    "    #for nn in range(NWEDGES):\n",
    "    #    print(MWP[idx[nn]])\n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        for nn in range(NWEDGES):\n",
    "            print(\"barred list, orig MWP, TWP\",BARREDLIST, r3(MWP[nn]),r3(TWP[nn]) )\n",
    "    \n",
    "    for nn in range(NWEDGES):  #going from least to most maxWedgePop here ...\n",
    "        nW = idx[nn]\n",
    "        if MWP[nW] < TWP[nW]: #need to redistribute extra target to higher-capacity wedges ...\n",
    "            wedgePopGap = TWP[nW] - MWP[nW]\n",
    "            TWP[nW] = MWP[nW]  #max out this wedge\n",
    "            nReceivers = 0.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....\n",
    "                    nReceivers += 1.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....                    \n",
    "                    TWP[WW] += wedgePopGap / nReceivers  #... so give it equal share of the gap, even if this goes over; we'll correct in later loop\n",
    "                    \n",
    "    WILLFILL = [1]*NWEDGES\n",
    "    for nW in range(NWEDGES):\n",
    "        if MWP[nW] < 1.001* TWP[nW]:  #required pop nearly or truly requires the entire wedge\n",
    "            WILLFILL[nW] = 0 \n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        print(\"adjusted TWP's are\",TWP)\n",
    "    return TWP, WILLFILL\n",
    "\n",
    "def solveWedge(nontractTWP,t, hC, STARTANGLE, ENDANGLE, MAXD, TOLERPOPS, tractCP, tractPop,\n",
    "               countyTractList, countyGeom, countyPop, neighborCountyLIST,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    #### NO LONGER USED; SEE FASTER SOLVEWEDGEB BASED ON UNIT-UNIT DISTANCES  *********\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop (which excludes the home tractPop)\n",
    "    The wedge has a fixed starting and ending angle.  Its maximum diameter is angle-related to max diameter of the state map\n",
    "    It uses bisection, NOT scipy minimize to minimize the square error in the wedge pop vs. target\n",
    "    The method passes back the final wedge pop and list of tracts in the wedge\n",
    "    \"\"\"\n",
    "    chgLoopNo, maxLoopNo = 10., 22.  #when we will start relaxing the pop tolerance, and when we give up\n",
    "    includedAngl = ENDANGLE - STARTANGLE\n",
    "    guessedR = MAXD / math.cos(0.5*includedAngl)  #max possible wedge radius, accounting for possible wide angle\n",
    "    popTol = TOLERPOPS[0]  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    #                      We loosen toward half the MAX tractPop if not converging\n",
    "    \n",
    "    offsetPop = 88888888.  #to force a reduction the first time through the loop\n",
    "    dr = guessedR\n",
    "    loopNo = 0\n",
    "    while abs(offsetPop) > popTol and loopNo < maxLoopNo:\n",
    "        loopNo +=1\n",
    "        popTol = max(TOLERPOPS[0], TOLERPOPS[0] + (TOLERPOPS[1] - TOLERPOPS[0]) * (loopNo - chgLoopNo) / (maxLoopNo - chgLoopNo) )\n",
    "        dr = 0.5*dr\n",
    "        guessedR -= dr*np.sign(offsetPop)\n",
    "        \n",
    "        guessedPoly = buildWedge(tractCP[t],STARTANGLE, ENDANGLE, guessedR,XSCALE) \n",
    "        iCP, iClist =  getCountyWP(t,guessedPoly, tractCP, tractPop, countyTractList[hC])\n",
    "        nonCP, nonClist = getNonCWP(guessedPoly, hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyLIST)\n",
    "        offsetPop = iCP + nonCP - nontractTWP\n",
    "        #print(t,loopNo,r5(guessedR),int(iCP),int(nonCP),r3(offsetPop+nontractTWP),r3(nontractTWP),\"t,loop,R,iCP,nonCP,pop,target\")\n",
    "        if loopNo >= maxLoopNo-1:\n",
    "            print(\"WARNING. Looped\",loopNo,\"times for t,angles,R\",t,r3(STARTANGLE),r3(ENDANGLE),r5(guessedR),\n",
    "                  \"wedgePop offset, target are\",int(offsetPop), int(nontractTWP) )    \n",
    "    finalPop = iCP + nonCP\n",
    "    finalList = iClist + nonClist\n",
    "    return finalPop, finalList, guessedR, loopNo\n",
    "\n",
    "#above = bisection.  Below solveWedgeB uses static unit-unit distances\n",
    "# Also tried scipy minimize, which doesn't seem any faster\n",
    "\n",
    "def solveWedgeB(nontractTWP,T, HC, POLLY, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that intersect,\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2x2 array\n",
    "    \"\"\"\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    \n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList = 0, 0, list()\n",
    "    notFull = True\n",
    "    while notFull :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist    \n",
    "\n",
    "def solveWedgeC(nontractTWP,T, HC, POLLY, STARTANGL, ENDANGL, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST, UUANGLE):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that\n",
    "    fall within the angle range (in lieu of wedgeB's check for intersection),\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2D array\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    STARTANGL, ENDANGL = STARTANGL % (2.*pi), ENDANGL % (2.*pi)\n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList, latestDist = 0, 0, list(), 0.00001  #dummy value\n",
    "    notFull = True\n",
    "    while notFull and i < len(UUDIST) - 2 :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if isIncludedA(STARTANGL, ENDANGL, UUANGLE[TT]) : #POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist \n",
    "\n",
    "\n",
    "def getPartialTract(t, HDTRACTLIST, offsetPop, UUDIST, tractPop, neighborLIST):\n",
    "    \"\"\"\n",
    "    If offsetPop is >0, this method identifies the tract with centroid farthest from Home t that can jettison at least offsetPop ...\n",
    "    ... by slicing out part of this tract.\n",
    "    If offsetPop <0, we ID a tract CLOSEST to Home t among neighbors of in-HD tracts to pick up a partial\n",
    "    We return the tractID and its new partial use\n",
    "    We have updated this method to pass the uuDist slice for tract t instead of computing tract distances inside here\n",
    "    \"\"\"\n",
    "    debugGPT = False\n",
    "    NTRACTS = len(tractCP)\n",
    "    bigDist = 9999999.\n",
    "    qualifyingTractList = list()\n",
    "    isWholeTract = False\n",
    "    if offsetPop > 0:\n",
    "        homeDist = [0.]*NTRACTS  #default = 0 to not get picked\n",
    "        for TT in HDTRACTLIST:\n",
    "            if tractPop[TT] > offsetPop:\n",
    "                qualifyingTractList.append(TT)\n",
    "        for TT in qualifyingTractList:\n",
    "            homeDist[TT] = UUDIST[TT]\n",
    "        if len(qualifyingTractList) == 0:  #very rare case where all in-HD tracts are too small.  Jettison nearly the whole farthest one\n",
    "            isWholeTract = True\n",
    "            for TT in HDTRACTLIST:\n",
    "                if tractPop[TT] > 0.9*np.average(tractPop): #set arbitrary min qualifying pop\n",
    "                    homeDist[TT] = UUDIST[TT]\n",
    "        targetT = homeDist.index(np.max(homeDist))\n",
    "        partialUseFrac = max(0.0001,(tractPop[targetT] - offsetPop)/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(\"positive offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    else: #pick up a partial\n",
    "        homeDist = [bigDist]*NTRACTS\n",
    "        for TT in HDTRACTLIST:\n",
    "            for TTT in neighborList[TT]:\n",
    "                if TTT not in qualifyingTractList and TTT not in HDTRACTLIST and tractPop[TTT] > abs(offsetPop):\n",
    "                    qualifyingTractList.append(TTT)\n",
    "        for TTT in qualifyingTractList:\n",
    "            homeDist[TTT] = UUDIST[TTT]\n",
    "        if len(qualifyingTractList) == 0 :  #rare case where most nearby tracts are small.  Add nearly the whole biggest one\n",
    "            isWholeTract = True\n",
    "            maxPop = 0.\n",
    "            targetT = -999\n",
    "            for TT in HDTRACTLIST:\n",
    "                for TTT in neighborList[TT]:\n",
    "                    if TTT not in qualifyingTractList and TTT not in HDTRACTLIST : # we'll take just one, even if doesn't fill gap\n",
    "                        qualifyingTractList.append(TTT)\n",
    "            for TTT in qualifyingTractList:\n",
    "                if tractPop[TTT] > maxPop:\n",
    "                    targetT = TTT\n",
    "                    maxPop = tractPop[targetT]\n",
    "        else:\n",
    "            targetT = homeDist.index(np.min(homeDist))\n",
    "        partialUseFrac = min(0.9999, -1.* offsetPop/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(t,\"'s negative offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    \n",
    "    return targetT, partialUseFrac\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:  #stop looping if no new neighbors found on previous loop\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=4):\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def avoidedEnclave(UNITLIST, UNITNBRS, ADDLIST,MAXLOOPS=15):  #20 is arbitrary, but does suppress slender chains\n",
    "    \"\"\"\n",
    "    This method (new for WI 5-23-24) is designed as a shorter check than enclaveCheck for legitimacy of adding ADDLIST to UNITLIST\n",
    "    It tries to find contiguity among all ADDLIST's neighbors that won't be in the UNITLIST after the add.\n",
    "    It does this in successive loops, growing from one non-UNITLIST neighbor in loops to all its non-UL neighbors\n",
    "    If success before MAXLOOPS, it returns True (i.e. this list addition avoided forming an enclave), else it returns False\n",
    "        Note that this method will not usually allow a UNITLIST that doesn't currently touch map border to start touching it\n",
    "        (too many loops to go all the way around the UNITLIST to find the complement's connection)\n",
    "    \"\"\"   \n",
    "    willBeInUnitSet = set(UNITLIST+ADDLIST)\n",
    "    nbrsOfADDLIST = set()\n",
    "    for U in ADDLIST:\n",
    "        nbrsOfADDLIST = nbrsOfADDLIST.union(set(UNITNBRS[U]))  #these are the neighbors of the units we plan to add to UNITLIST\n",
    "    nbrsOfADDLIST = nbrsOfADDLIST.difference(willBeInUnitSet)\n",
    "    if len(nbrsOfADDLIST) == 0:\n",
    "        print(\"Warning! Attempted to add list\",ADDLIST,\"but it looks like an enclave\") #formerly an exception\n",
    "        return False\n",
    "    firstNo = next(iter(nbrsOfADDLIST))  #pick one of these non-UL neighbors as a starter\n",
    "    firstGroup = getContigFromStarter(firstNo, nbrsOfADDLIST, UNITNBRS) #first find all neighbors that directly connect\n",
    "    foundNbrSet, foundTotalSet, newFoundSet = set(firstGroup),set(firstGroup),set(firstGroup)\n",
    "    LOOPNO = 0\n",
    "    stillConnect = False\n",
    "    if len(foundNbrSet) == len(nbrsOfADDLIST):  #ALL non-UNITLIST neighbors still DIRECTLY connect after the add\n",
    "        stillConnect = True\n",
    "    while len(newFoundSet) > 0 and LOOPNO <= MAXLOOPS and not stillConnect:\n",
    "        LOOPNO +=1\n",
    "        lastFoundSet = newFoundSet\n",
    "        newFoundSet = set()\n",
    "        for U in lastFoundSet:\n",
    "            newFoundSet = newFoundSet.union(set(UNITNBRS[U]))\n",
    "        newFoundSet = newFoundSet.difference(willBeInUnitSet)\n",
    "        \n",
    "        foundTotalSet = foundTotalSet.union(newFoundSet)\n",
    "        foundNbrSet = foundTotalSet.intersection(nbrsOfADDLIST)  #running list of complement-connectable non-UL neighbors of ADDLIST\n",
    "        if len(foundNbrSet) == len(nbrsOfADDLIST):  #ALL non-UNITLIST neighbors still connect after the add\n",
    "            stillConnect = True\n",
    "    return stillConnect\n",
    "              \n",
    "\n",
    "def avoidedIsland(UNITLIST, UNITNBRS, SHEDLIST,MAXLOOPS=15):\n",
    "    \"\"\"\n",
    "    analogous to avoidedEnclave but for shedding a list from UNITLIST; we look to connect in-UNITLIST neighbors after the proposed shed\n",
    "    \"\"\"\n",
    "    shrunkSet = set(UNITLIST).difference(set(SHEDLIST))  #shorthand for the proposed unitlist after shedding\n",
    "    nbrsOfSHEDLIST = set()\n",
    "    for U in SHEDLIST:\n",
    "        nbrsOfSHEDLIST = nbrsOfSHEDLIST.union(set(UNITNBRS[U]))\n",
    "    nbrsOfSHEDLIST = nbrsOfSHEDLIST.intersection(shrunkSet)\n",
    "    giveUp = False\n",
    "    if len(nbrsOfSHEDLIST) == 0:\n",
    "        giveUp = True  #rarely, the shedlist is contiguous but creates a weird contiguity problem (surrounds?).  Punt.\n",
    "        return False\n",
    "        #raise Exception(\"ERROR! Attempted to shed list\",SHEDLIST,\"but it was never connected to the rest of the unit list\")\n",
    "    firstNo = next(iter(nbrsOfSHEDLIST))  #pick one of these still-in-UL neighbors as a starter   \n",
    "    firstGroup = getContigFromStarter(firstNo, nbrsOfSHEDLIST, UNITNBRS) #first find all neighbors that directly connect\n",
    "    foundNbrSet, foundTotalSet, newFoundSet = set(firstGroup),set(firstGroup),set(firstGroup)\n",
    "    LOOPNO = 0\n",
    "    stillConnects = False\n",
    "    if len(foundNbrSet) == len(nbrsOfSHEDLIST):  #ALL in-UNITLIST neighbors of the shedlist still DIRECTLY connect after the shed\n",
    "        stillConnects = True\n",
    "    while len(newFoundSet) > 0 and LOOPNO <= MAXLOOPS and not stillConnects and not giveUp:\n",
    "        LOOPNO +=1\n",
    "        lastFoundSet = newFoundSet\n",
    "        newFoundSet = set()\n",
    "        for U in lastFoundSet:\n",
    "            newFoundSet = newFoundSet.union(set(UNITNBRS[U]))\n",
    "        newFoundSet = newFoundSet.intersection(shrunkSet)\n",
    "        \n",
    "        foundTotalSet = foundTotalSet.union(newFoundSet)\n",
    "        foundNbrSet = foundTotalSet.intersection(nbrsOfSHEDLIST)\n",
    "        if len(foundNbrSet) == len(nbrsOfSHEDLIST):  #all in-UNITLIST neighbors still connect after the shed\n",
    "            stillConnects = True\n",
    "    return stillConnects\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 6, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d041d328-83e0-45db-a869-e0956c23ee26",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the state postal code; e.g. OH  MO\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, enter 1 below to use mo_pl2020_vtd.dbf as this state's population data file\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "  1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempting to read in state unit geometries.  Stand by ...\n",
      "I read in the Census popn data. MO has 6154913 peeps and is divided into 4604 shapes.\n"
     ]
    }
   ],
   "source": [
    "STATE = str(input(\"Enter the state postal code; e.g. OH \")).upper()\n",
    "popFilename = STATE.lower()+\"_pl2020_vtd.dbf\"\n",
    "print(\"OK, enter 1 below to use\",popFilename,\"as this state's population data file\")\n",
    "enter1 = input(\" \")\n",
    "if int(enter1) != 1:\n",
    "    popFilename = input(\"OK, then enter the pop data file.  Typically a xx_pl2020_vtd.dbf\")\n",
    "print(\"attempting to read in state unit geometries.  Stand by ...\")\n",
    "tractPopFile = gpd.read_file(\"state_map_files/\"+popFilename)\n",
    "trueTractGeom = tractPopFile['geometry']\n",
    "nTracts = len(trueTractGeom)\n",
    "tractPop = tractPopFile['P0010001']\n",
    "statePop = np.sum(tractPop)\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "print(\"I read in the Census popn data.\",STATE,\"has\",statePop,\"peeps and is divided into\",nTracts,\"shapes.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3bfdea9d-b0ea-497a-a556-6b488a3e333e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the number of districts in the state.  My guess is 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 115 counties in MO .  I will assign them county Nos 0 - 114\n"
     ]
    }
   ],
   "source": [
    "tractGeom = trueTractGeom.copy()   #for some states, we will modify geom, so preserve original\n",
    "#tractNAME20 = tractPopFile['NAME20']\n",
    "tractPop = tractPopFile['P0010001']\n",
    "tractVAP = tractPopFile['P0030001']\n",
    "tractWhiteVAP = tractPopFile['P0030003']  #this is within 2% of VEST's vap_white\n",
    "inputfileCountyNo = tractPopFile['COUNTYFP20']\n",
    "vtdGEOID20 =  tractPopFile['GEOID20'] \n",
    "nDistricts = int(round(statePop/760000,0))\n",
    "nCutDistricts = 0\n",
    "nDistricts = int(input(\"Enter the number of districts in the state.  My guess is \"+str(nDistricts)))\n",
    "tractArea = [tractGeom[t].area for t in range(nTracts)]\n",
    "trueTractCP =   [tractGeom[t].centroid for t in range(nTracts)]\n",
    "tractCP = trueTractCP.copy()  #for some states, we move secluded corners into the map, so save the true data\n",
    "tractCPx =  [tractCP[t].x for t in range(nTracts)]\n",
    "tractCPy =  [tractCP[t].y for t in range(nTracts)]\n",
    "inputCountyNumbers = list()\n",
    "for t in range(nTracts):\n",
    "    if inputfileCountyNo[t] not in inputCountyNumbers:\n",
    "        inputCountyNumbers.append(inputfileCountyNo[t])\n",
    "nCounties = len(inputCountyNumbers)\n",
    "print(\"There appear to be\",nCounties,\"counties in\",STATE,\".  I will assign them county Nos 0 -\",int(nCounties-1))\n",
    "sortedICNs = list(np.sort(inputCountyNumbers))\n",
    "countyNo = [sortedICNs.index(inputfileCountyNo[t]) for t in range(nTracts) ]\n",
    "\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "adffc7a4-a78c-477f-8ea4-7f8e5109fa2a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now build the county-by-county geometries, hoping there are no islands\n",
      "Building county geom for county 0\n",
      "Building county geom for county 20\n",
      "Building county geom for county 40\n",
      "Building county geom for county 60\n",
      "Building county geom for county 80\n",
      "Building county geom for county 100\n",
      "Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop < 4.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 0 unpopulated coastal tracts.\n"
     ]
    }
   ],
   "source": [
    "print(\"We will now build the county-by-county geometries, hoping there are no islands\")\n",
    "skipList = list()  #a list of units we previously know to skip in the map\n",
    "isAlteredCounty = [False for c in range(nCounties)]\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "countyPop =       [0. for c in range(nCounties)]\n",
    "countyGeom =      [dummyPoly for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    if t not in skipList:\n",
    "        c = countyNo[t]\n",
    "        countyTractList[c].append(t)\n",
    "        countyPop[c] += tractPop[t]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Building county geom for county\",c)\n",
    "    for t in countyTractList[c]:\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            countyGeom[c] = tractGeom[t]\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "origMAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    origMAP = origMAP.union(countyGeom[c])\n",
    "    if countyGeom[c] == dummyPoly:\n",
    "        print(\"WARNING! county\",c,\"is empty!\")\n",
    "    else:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "minTractPop = 4.5\n",
    "print(\"Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop <\",minTractPop)\n",
    "plt.show()\n",
    "if origMAP.geom_type == dummyPoly.geom_type:\n",
    "    mapExterior = origMAP.exterior\n",
    "else:\n",
    "    for i,geo in enumerate(origMAP.geoms):\n",
    "        if i == 0:\n",
    "            mapExterior = geo.exterior\n",
    "        else:\n",
    "            mapExterior = mapExterior.union(geo.exterior)\n",
    "\n",
    "for c in range(nCounties):\n",
    "    for t in countyTractList[c]:\n",
    "        if tractPop[t] < minTractPop:\n",
    "            if tractGeom[t].intersects(mapExterior):\n",
    "                isAlteredCounty[c] = True\n",
    "                skipList.append(t)\n",
    "print(\"There appear to be\",len(skipList),\"unpopulated coastal tracts.\")\n",
    "if len(skipList) > 0:\n",
    "    print(\"Lets plot them and their parent counties\")\n",
    "    for t in skipList:\n",
    "        plotPoly(tractGeom[t])\n",
    "        plotCenter(t,tractGeom[t],6)\n",
    "    plotPoly(origMAP,0.2)\n",
    "    for c in range(nCounties):\n",
    "        if isAlteredCounty[c]:\n",
    "            plotPoly(countyGeom[c])\n",
    "    plt.show()\n",
    "trueMAP = origMAP  #use these terms interchangeably"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a6c93c4-af08-47d5-90f7-dc0b4513aad5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last chance to alter the skipList, otherwise the above 0 units will be axed\n",
      "here is the proposed skipList []\n",
      "here is the final skipList []\n"
     ]
    }
   ],
   "source": [
    "print(\"Last chance to alter the skipList, otherwise the above\",len(skipList),\"units will be axed\")\n",
    "print(\"here is the proposed skipList\", skipList)\n",
    "#skipList = [146, 3084] #...  #alter here if needed - nothing for MO\n",
    "print(\"here is the final skipList\", skipList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2989f381-466b-4882-bf1d-cfa37a7ba8ef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now preserve the original county unit lists and geoms, then rebuild as needed\n",
      "Here is the revised state county map after eliminating coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excellent!  We have no populated islands.  SKIP the below code block.\n",
      "we will scale longitudinal distance by 0.78447\n"
     ]
    }
   ],
   "source": [
    "print(\"I will now preserve the original county unit lists and geoms, then rebuild as needed\")\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "trueCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    trueCountyTractList[c] = countyTractList[c].copy()\n",
    "    if isAlteredCounty[c]:\n",
    "        print(\"removing coastal units from countyNo\",c)\n",
    "        countyTractList[c] = list()\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in trueCountyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                countyTractList[c].append(t)\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            print(\"Uh oh! county\",c,\"didn't have any usable tracts\")\n",
    "MAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c])\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "origPopMAP = MAP   #origPopMAP is the map after eliminating coastal unpopulated tracts, with original islands\n",
    "print(\"Here is the revised state county map after eliminating coastal tracts\")\n",
    "plt.show()\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    print(\"Excellent!  We have no populated islands.  SKIP the below code block.\")\n",
    "else:\n",
    "    print(\"We appear to have some populated islands.  Separate out the main state geom in next block.\")\n",
    "LAT = MAP.centroid.y\n",
    "xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "print(\"we will scale longitudinal distance by\",r5(xScale))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37da9a52-6da3-41e1-a103-110fb4c5476f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#deleted island triage code ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4aebe4ee-ee7b-4bf3-8413-f315556d453e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing all county centerpoints, then plot them\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"computing all county centerpoints, then plot them\")\n",
    "countyCP  = list()\n",
    "cutCountyList = list()\n",
    "for c in range(nCounties):\n",
    "    cTL = countyTractList[c]\n",
    "    countyCP.append(getHDcp( [tractCP[v] for v in cTL], [tractPop[v] for v in cTL], [i for i in range(len(cTL) ) ] ) )\n",
    "    if countyCP[c].disjoint(countyGeom[c]):  #possible with weird-shaped county\n",
    "        countyCP[c] = nearest_points(countyGeom[c],countyCP[c])[0]\n",
    "    plotPoly(countyCP[c].buffer(0.03))\n",
    "    plotPoly(countyGeom[c],0.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "207f3a55-e361-4777-ae46-41fe3d54a4b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This code block reads in a csv with whole districts to be cut out of the map\n",
      "For MO my input file says to cut out 0 districts out of 8\n",
      "There were no cut districts in MO\n"
     ]
    }
   ],
   "source": [
    "print(\"This code block reads in a csv with whole districts to be cut out of the map\")\n",
    "unclippedMAP = MAP\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "nCutDistricts = nCuts\n",
    "nStops = trimDF[\"nStopLines\"][DFrow]\n",
    "nDistricts = trimDF[\"nDistricts\"][DFrow]\n",
    "stopLines = list()  #the 'stoplines' stop wedge growth that hops across concave map areas (not currently used)\n",
    "cutCountyList = list()\n",
    "allCutLists, allCutPops = list(), list()\n",
    "print(\"For\",STATE,\"my input file says to cut out\",nCuts,\"districts out of\",nDistricts)\n",
    "if nCuts > 0:\n",
    "    cutList = list()\n",
    "    cutXs = ast.literal_eval(trimDF[\"cutXs\"][DFrow])\n",
    "    cutYs = ast.literal_eval(trimDF[\"cutYs\"][DFrow])\n",
    "    cutPoints = [Point(cutXs[i],cutYs[i]) for i in range(len(cutXs)) ]\n",
    "    for cutNo in range(nCuts):\n",
    "        print(\"performing cut no\",cutNo,\"for state\",STATE)  #first two cutPoints must form the cutLine\n",
    "        cutNotDone = True\n",
    "        thisCutPoints = [ cutPoints[int(4*cutNo)],cutPoints[int(4*cutNo+1)],cutPoints[int(4*cutNo+2)],cutPoints[int(4*cutNo+3)]  ]\n",
    "        while cutNotDone:\n",
    "            cutPoly = Polygon([thisCutPoints[0],thisCutPoints[1],thisCutPoints[2],thisCutPoints[3] ])\n",
    "            cutLine = LineString([thisCutPoints[0], thisCutPoints[1] ] )\n",
    "            cutList = list()\n",
    "            cutPop = 0.\n",
    "            for c in range(nCounties):\n",
    "                if cutPoly.intersects(countyGeom[c]):\n",
    "                    if cutPoly.contains(countyGeom[c]):\n",
    "                        cutList = cutList + countyTractList[c]\n",
    "                        cutPop += countyPop[c]\n",
    "                    else:\n",
    "                        for t in countyTractList[c]:\n",
    "                            if cutPoly.contains(tractCP[t]):\n",
    "                                cutList.append(t)\n",
    "                                cutPop += tractPop[t]\n",
    "                            if STATE == \"NC\":\n",
    "                                if t == 1828:\n",
    "                                    print(\"special for NC - include vtd 1828 from county 55 in the cut list for contiguity\")\n",
    "                                    cutList.append(t)\n",
    "                                    cutPop += tractPop[t]\n",
    "            print(\"the total proposed cutPop is\",cutPop,\". Compare to\",int(statePop/nDistricts) )\n",
    "\n",
    "            doIcut = input(\"enter 1 to apply the cut\")\n",
    "            if str(doIcut) == str(1):\n",
    "                cutNotDone = False\n",
    "                allCutLists.append(cutList)\n",
    "                allCutPops.append(cutPop)\n",
    "            else:\n",
    "                print(\"Here is the state and the last proposed cutPoly.\")\n",
    "                plotPoly(cutPoly)\n",
    "                plotPoly(MAP)\n",
    "                plt.show()\n",
    "                print(cutPoly)\n",
    "                oldPts = list(cutPoly.exterior.coords)\n",
    "                newPtXs = ast.literal_eval(input(\"enter alternate [ x0, x1 ] for the first two points\") )\n",
    "                newPtYs = ast.literal_eval(input(\"enter alternate [ y0, y1 ] for the first two points\") )\n",
    "                thisCutPoints = [Point(newPtXs[0],newPtYs[0]), Point(newPtXs[1],newPtYs[1]),oldPts[2], oldPts[3] ]\n",
    "allCutVTDs = list()\n",
    "for L in allCutLists:\n",
    "    for v in L:\n",
    "        allCutVTDs.append(v)\n",
    "if nCutDistricts == 0:\n",
    "    print(\"There were no cut districts in\",STATE)\n",
    "else:\n",
    "    print(\"here are your cut districts\")\n",
    "    plotPoly(MAP)\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        cutGeo = tractGeom[L[0]]\n",
    "        for v in L:\n",
    "            cutGeo=cutGeo.union(tractGeom[v])\n",
    "        plotPoly(cutGeo,2)\n",
    "        plotCenter(i,cutGeo)\n",
    "        plotCenter(allCutPops[i],Point(cutGeo.centroid.x,cutGeo.centroid.y-0.5) )\n",
    "    plt.show()\n",
    "CCBlistString = trimDF[\"CCB counties\"][DFrow]\n",
    "CCBlist = ast.literal_eval(CCBlistString)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4c915415-6c44-4c43-9826-b565cebed95a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Write the vtd cutlists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Write the vtd cutlists to a file\")\n",
    "cutDistrictNo = list()\n",
    "for v in allCutVTDs:\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        if v in L:\n",
    "            cutDistrictNo.append(i)\n",
    "            break\n",
    "nbrDF = pd.DataFrame( {\"vtdNo\":allCutVTDs,\"cutDistrictNo\":cutDistrictNo} )\n",
    "outname = STATE+\"wholeDistrictCuts.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "nbrDF.to_csv(outpath)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "17721728-e5c0-4787-b430-9d7d94970667",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8 districts\n"
     ]
    }
   ],
   "source": [
    "countyPop = [0. for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    countyPop[countyNo[t]] += tractPop[t]\n",
    "print(nDistricts,\"districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f3073320-8d92-45ba-beb2-fb8c08d7170d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed all whole districts.  Finalize stats before squishing in outcroppings.\n",
      "Of the total statePop 6154913.0 we ignore 0.0 as it is cut out of the map\n",
      "This excluded pop comes from a total of 0 tracts\n",
      "Our final adjusted number of state districts, excluded fixed cut-out is 8 rather than original 8\n",
      "Each district will be drawn to house 769364.125 = 1/ 8 of non-cutout state pop 6154913.0 vs original= 6154913.0\n",
      "Here is a county-level modified map with each county's fraction of a district pop\n",
      "working on county 0\n",
      "working on county 20\n",
      "working on county 40\n",
      "working on county 60\n",
      "working on county 80\n",
      "working on county 100\n",
      "here is the MO map excluding cut and unpop coastal tracts\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Removed all whole districts.  Finalize stats before squishing in outcroppings.\")\n",
    "trueCountyPop = [countyPop[c] for c in range(nCounties)]\n",
    "trueCountyGeom = countyGeom.copy()\n",
    "countyPop = [0. for c in range(nCounties)]\n",
    "trueStatePop, true_nDistricts = np.sum(trueCountyPop), nDistricts\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "# minTractPop = 4.5  #already defined above\n",
    "populatedTractList = list()\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "statePop, excludedPop = 0., 0.\n",
    "\n",
    "for t in range(nTracts):\n",
    "    trueCountyTractList[countyNo[t]].append(t)\n",
    "    if t in allCutVTDs or t in skipList:  #  or vtdPop[t] < minTractPop:  #need to keep low-pop vtds as VEST may have assigned votes to them\n",
    "        excludedPop += tractPop[t]\n",
    "    else:\n",
    "        populatedTractList.append(t)\n",
    "        countyTractList[countyNo[t]].append(t)\n",
    "        countyPop[countyNo[t]] += tractPop[t]\n",
    "        statePop += tractPop[t]\n",
    "        #tractPop[t] = max(tractPop[t],0.000001)  #avoid possible later div/zero errors for nil-vote vtds\n",
    "print(\"Of the total statePop\",statePop+excludedPop,\"we ignore\",excludedPop,\"as it is cut out of the map\") #,\n",
    "#\"or in sparsely populated areas (<\",minTractPop,\") per geom\")\n",
    "print(\"This excluded pop comes from a total of\",nTracts -len(populatedTractList),\"tracts\")\n",
    "true_nDistricts = nDistricts\n",
    "nDistricts -= nCutDistricts\n",
    "print(\"Our final adjusted number of state districts, excluded fixed cut-out is\",nDistricts,\"rather than original\",true_nDistricts)\n",
    "aDP = statePop/float(nDistricts)\n",
    "print(\"Each district will be drawn to house\",r3(aDP),\"= 1/\",nDistricts,\"of non-cutout state pop\",statePop,\"vs original=\",trueStatePop)\n",
    "print(\"Here is a county-level modified map with each county's fraction of a district pop\")\n",
    "\n",
    "vtdGeom = tractGeom.copy()\n",
    "nVTDs = len(vtdGeom)\n",
    "\n",
    "cutCountyList, uncutCountyList = list(), list()\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on county\",c)\n",
    "    if len(countyTractList[c]) == 0:  #no vtds added to county b/c all were in cut lists:\n",
    "        cutCountyList.append(c)\n",
    "    else:\n",
    "        uncutCountyList.append(c)\n",
    "        countyGeom[c] = tractGeom[countyTractList[c][0]]\n",
    "        for t in countyTractList[c]:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "uncutMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "print(\"here is the\",STATE,\"map excluding cut and unpop coastal tracts\")\n",
    "\n",
    "for c in uncutCountyList:\n",
    "    plotPoly(countyGeom[c])\n",
    "    FONTSIZE = 8 #11  #reduce for TX\n",
    "    if countyPop[c] / statePop < 0.02:\n",
    "        FONTSIZE = 5 #7 #reduce for TX\n",
    "        plotCenter(r3(countyPop[c]/aDP),countyGeom[c], FONTSIZE)\n",
    "    else:\n",
    "        plotCenter(round(countyPop[c]/aDP,2),countyGeom[c], FONTSIZE)\n",
    "plotPoly(trueMAP,0.1)\n",
    "for c in cutCountyList:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "    plotCenter(\"cut\",countyGeom[c],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0062ac21-3328-4616-99ed-70c53e62b308",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the map topology before any squish operations.  Plot countyPop/aDP\n",
      "Working on county  0 distances\n",
      "Working on county  20 distances\n",
      "Working on county  40 distances\n",
      "Working on county  60 distances\n",
      "Working on county  80 distances\n",
      "Working on county  100 distances\n",
      "the max LAT-scaled distance between counties is 6.14182\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter user-picked max district diameter, or 0 to accept 6.14182  0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on county  0 neighbors\n",
      "Working on county  20 neighbors\n",
      "Working on county  40 neighbors\n",
      "Working on county  60 neighbors\n",
      "Working on county  80 neighbors\n",
      "Working on county  100 neighbors\n",
      "I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#For corners and outcroppings, we fuse county clusters\n",
    "collapsedCountyList = list()  #VA has independent cities that we will reassign to parent counties\n",
    "print(\"Now finalize the map topology before any squish operations.  Plot countyPop/aDP\")\n",
    "preSquishCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "maxD = 0.\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"distances\")\n",
    "    if c not in cutCountyList:\n",
    "        plotPoly(countyGeom[c],0.2)\n",
    "        plotCenter(r3(countyPop[c]/aDP), countyGeom[c], 7 )\n",
    "        for cc in range(c+1, nCounties):\n",
    "            dist = getLongDist(countyCP[c],countyCP[cc],xScale)\n",
    "            if dist > maxD and cc not in cutCountyList:\n",
    "                maxD = dist\n",
    "                #print(c,cc,maxD)\n",
    "print(\"the max LAT-scaled distance between counties is\",r5(maxD))\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAP.centroid.buffer(0.5*maxD))\n",
    "plt.show()\n",
    "inputD = float( input(\"enter user-picked max district diameter, or 0 to accept \"+str(r5(maxD))+\" \") )\n",
    "if inputD > 0:\n",
    "    maxD = inputD\n",
    "neighborCountyList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"neighbors\")\n",
    "    for cc in uncutCountyList:\n",
    "        if cc > c and cc not in cutCountyList:  \n",
    "            if countyGeom[c].intersects(countyGeom[cc]) :\n",
    "                neighborCountyList[c].append(cc)\n",
    "                neighborCountyList[cc].append(c)\n",
    "print(\"I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\")\n",
    "hasFewNeighborCs, has1neighborCs = list(), list()\n",
    "plotPoly(MAP,0.15)\n",
    "for c in uncutCountyList:\n",
    "    if len(neighborCountyList[c]) == 2:\n",
    "        hasFewNeighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.2,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.5)\n",
    "    if len(neighborCountyList[c]) < 2:\n",
    "        has1neighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.1,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "398fbc6d-3b05-4c1f-87cb-72d11cdd98bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "useCCBlist = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f9b3df93-d821-44ca-b4f4-b65d13baaffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will use the cutNClip csv list of corner-county bundles\n",
      "Our final pops and fused-county lists are...\n",
      "161018.0 [2, 43, 73, 1, 112, 37, 10, 31, 40]\n",
      "185562.0 [59, 72, 4, 54, 103]\n",
      "139686.0 [77, 34, 71, 66, 99, 102]\n",
      "25126.0 [22, 98, 55, 51]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aDP = float(statePop)/nDistricts\n",
    "if useCCBlist:\n",
    "    print(\"We will use the cutNClip csv list of corner-county bundles\")\n",
    "    nCCBs = len(CCBlist)\n",
    "    CCBpop, CCBgeom = [0.]*nCCBs, [countyGeom[L[0]] for L in CCBlist]\n",
    "    for i, L in enumerate(CCBlist):\n",
    "        for cc in L:\n",
    "            CCBpop[i] += countyPop[cc]\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[cc])\n",
    "else:\n",
    "    maxCCBratio = 1./4.  #adjustable max fraction of district pop for corner county blocks.  Let's try 3/16\n",
    "    maxCCBpop = maxCCBratio * aDP\n",
    "    print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "    CCBlist, CCBpop, passThruList = list(), list(), list()  #\"waiveThru\" counties get chance to join a cluster even if high pop\n",
    "    nFuses = 0\n",
    "    for c in set(has1neighborCs).difference(set(collapsedCountyList)):\n",
    "        print(\"checking if county\",c,\"with pop\",countyPop[c],\"and only 1 neighbor is less pop than\",int(maxCCBpop),\"vs districtPop\",int(aDP) )\n",
    "        if countyPop[c] > maxCCBpop:\n",
    "            plotPoly(countyGeom[c])\n",
    "            plotCenter(c,countyGeom[c])\n",
    "            nc = neighborCountyList[c][0]\n",
    "            plotPoly(countyGeom[nc],0.5)\n",
    "            plotPoly(MAP,0.2)\n",
    "            print(\"county\",c,\"has pop\",countyPop[c],\"and its only neighbor has pop\",countyPop[nc],\"vs districtPop\",aDP,\". Default = keep un-fused\")\n",
    "            print(\"enter 0 to keep\",c,\"as an unfused collection of units, 1 to fuse as one unit and stop, 2 to force-add at least the next closest county\")\n",
    "            fuseChoice = input(\"0, 1, or 2.  Any other input taken as a zero\")\n",
    "            if fuseChoice == 0:\n",
    "                keepUnfused = True\n",
    "                break\n",
    "            elif int(fuseChoice) == 1:\n",
    "                CCBlist.append([c])\n",
    "                CCBpop.append(countyPop[c])  \n",
    "                hasFewNeighborCs.append(c)  #this adds this [c] to the final list of fused units, but will fail to find more in below\n",
    "            elif int(fuseChoice) == 2:\n",
    "                CCBlist.append([c,nc ] )\n",
    "                CCBpop.append(countyPop[c] + countyPop[nc])\n",
    "                hasFewNeighborCs.append(c)\n",
    "                passThruList.append(c)   #pass on thru to the below 2neighbor logic even if too high-pop to qualify\n",
    "        else:\n",
    "            hasFewNeighborCs.append(c)  #normal case; we'll handle in next, more general, for loop            \n",
    "            \n",
    "    for c in set(hasFewNeighborCs).difference(set(collapsedCountyList)):\n",
    "        print(\"checking if county\",c,\"with pop\",countyPop[c],\"and 1 or 2 neighbors is less pop than\",int(maxCCBpop) )\n",
    "        if countyPop[c] < maxCCBpop :\n",
    "            CCBlist.append([c])\n",
    "            CCBpop.append(countyPop[c])\n",
    "            CCBno = CCBlist.index([c])\n",
    "        if c in passThruList:\n",
    "            CCBno = CCBlist.index([c,neighborCountyList[c][0] ])\n",
    "        if countyPop[c] < maxCCBpop or c in passThruList:            \n",
    "            CCBstarter = c\n",
    "            canAdd = True\n",
    "            while canAdd:\n",
    "                nbrSet = set()\n",
    "                for cc in CCBlist[CCBno]:\n",
    "                    nbrSet = ( nbrSet.union(set(neighborCountyList[cc])) ).difference(set(CCBlist[CCBno]))\n",
    "                nPop = [countyPop[cc] for cc in nbrSet]\n",
    "                nDist = [countyGeom[cc].centroid.distance(countyGeom[CCBstarter].centroid) for cc in nbrSet]\n",
    "                idx = np.argsort(nDist)\n",
    "                nbrList, newList = list(nbrSet), list()\n",
    "                for i in range(len(nDist)):  #add counties, closest to starter that will fit until over\n",
    "                    cc = nbrList[idx[i]]\n",
    "                    if CCBpop[CCBno] + countyPop[cc] < maxCCBpop:\n",
    "                        newList.append(cc)\n",
    "                        CCBlist[CCBno].append(cc)\n",
    "                        CCBpop[CCBno] += countyPop[cc]\n",
    "                        #print(\"adding county\",cc,\"with pop\",countyPop[cc],\"to list started by\",CCBstarter,\".Cluster pop now\",CCBpop[CCBno]  )\n",
    "                if newList == list():  #no eligible neighbor counties found; stop\n",
    "                    canAdd = False\n",
    "                    for cc in CCBlist[CCBno]:\n",
    "                        plotPoly(countyGeom[cc])\n",
    "                        plotCenter(CCBno,countyGeom[cc])\n",
    "    plotPoly(MAP,0.2)\n",
    "    plt.show()\n",
    "                        \n",
    "    print(\"Below I plot these again by county no, with faded neighboring counties\")\n",
    "    plotPoly(MAP,0.15)\n",
    "    for L in CCBlist:\n",
    "        print(CCBlist.index(L),\" \",L)\n",
    "        for c in L:\n",
    "            plotPoly(countyGeom[c])\n",
    "            plotCenter(c,countyGeom[c])\n",
    "            for cc in list(set(neighborCountyList[c]).difference(L) ):\n",
    "                plotPoly(countyGeom[cc],0.4)\n",
    "                plotCenter(cc,countyGeom[cc],8)\n",
    "    plt.show()\n",
    "    rejectList = list()\n",
    "    print(\"Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are\",r3(aDP), int(maxCCBpop))\n",
    "    print(\"You may suggest [[2,43,73,1,112,37,10,31,40], [59,72,4,54,103], [77,34,71,66,99,102], [22,98,55,51] ] \")\n",
    "    for i,L in enumerate(CCBlist):\n",
    "        if L[0] not in passThruList:  #if we forced the fused-counties list above, don't give option here to modify\n",
    "            print(\"let's decide whether to delete, accept, or modify list\",L,\"with pop\",CCBpop[i] )\n",
    "            isOK = input(\"enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list)\")\n",
    "            if not (isOK == 1 or isOK == str(1)) :\n",
    "                if isOK == 0 or isOK == str(0) :\n",
    "                    rejectList.append(L)\n",
    "                else:\n",
    "                    notGood = True\n",
    "                    while notGood:       \n",
    "                        Lnew = ast.literal_eval(isOK)        \n",
    "                        if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                            notGood = False\n",
    "                        else:\n",
    "                            print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                            isOK = input(\"Try again here \")\n",
    "                    print(\"OK, I will replace\",L,\"with\",Lnew)\n",
    "                    CCBpop[i] = np.sum( [countyPop[c] for c in Lnew] )\n",
    "                    CCBlist[i] = Lnew.copy()\n",
    "    for L in rejectList:\n",
    "        del CCBpop[ CCBlist.index(L)]\n",
    "        del CCBlist[CCBlist.index(L)]\n",
    "    stillAdding = True\n",
    "    while stillAdding:\n",
    "        addMore = input(\"enter 1 if you want to manually add another corner-county cluster\")\n",
    "        if int(addMore) != 1:\n",
    "            stillAdding = False\n",
    "        else:\n",
    "            isOK = input(\"Type in a [county list], where the corner county is first in the list.  Or type 0 to stop\")\n",
    "            if isOK == 0 or isOK == str(0) :\n",
    "                print(\"OK, we'll stop adding corner clusters\")\n",
    "                stillAdding = False\n",
    "            else:\n",
    "                notGood = True\n",
    "                while notGood:       \n",
    "                    Lnew = ast.literal_eval(isOK)        \n",
    "                    if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                        notGood = False\n",
    "                        for L in CCBlist:\n",
    "                            if set(L).intersection(set(Lnew)) != set(list()) :\n",
    "                                notGood = True\n",
    "                                print(\"OOPS! The following inputted counties are already in\",L,\":\",set(L).intersection(set(Lnew)) )\n",
    "                                isOK = input(\"Try again here \")\n",
    "                        if notGood == False:\n",
    "                            CCBlist.append(Lnew)\n",
    "                            CCBpop.append( np.sum( [countyPop[c] for c in Lnew] ) )\n",
    "                    else:\n",
    "                        print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                        isOK = input(\"Try again here \")\n",
    "print(\"Our final pops and fused-county lists are...\")\n",
    "allFusedCounties = list()\n",
    "CCBgeom = [dummyPoly for L in CCBlist ]\n",
    "CCBcp = list()\n",
    "for i, L in enumerate(CCBlist):\n",
    "    CCBcp.append( getHDcp([countyCP[c] for c in L], [countyPop[c] for c in L], [ j for j in range(len(L)) ] ) )\n",
    "    print(CCBpop[i],L)\n",
    "    pops, CPs = list(), list()\n",
    "    for c in L:\n",
    "        if c == L[0]:\n",
    "            CCBgeom[i] = countyGeom[c]\n",
    "        else:\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[c])\n",
    "        allFusedCounties.append(c)\n",
    "        pops += countyPop[c]       #  IS THIS EVEN USED?\n",
    "        CPs.append(countyCP[c])   #  IS THIS EVEN USED?\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(i,countyGeom[c])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "206c9372-8ec8-4190-93ed-04df286466e0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now identify the border counties + border fused units, and interior small counties with pop < 15387\n",
      "We defined a total of 37 unit (but not corner-cluster) counties in the map\n",
      "excluding the cut-out districts and collapsed counties\n"
     ]
    }
   ],
   "source": [
    "maxWholeBorderCountyPop = 0.02 * aDP   #to encourage contiguity, border counties > 0.02 aDP will be forced whole\n",
    "maxInteriorBorderCountyPop = 0.02 * aDP\n",
    "print(\"now identify the border counties + border fused units, and interior small counties with pop <\", int(maxInteriorBorderCountyPop))\n",
    "unitCounties, borderCounties = list(), list()\n",
    "origMAP = MAP\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    MAPexterior = MAP.exterior\n",
    "else:\n",
    "    maxArea = 0\n",
    "    for geo in MAP.geoms:\n",
    "        if geo.area > maxArea:\n",
    "            MAPexterior = geo.exterior\n",
    "            maxArea = geo.area\n",
    "            MAP0 = geo\n",
    "    MAP = MAP0\n",
    "for c in set(uncutCountyList).difference(set(collapsedCountyList)):\n",
    "    if countyGeom[c].intersects(MAPexterior):\n",
    "        borderCounties.append(c)\n",
    "        if c not in allFusedCounties:\n",
    "            if countyPop[c] < maxWholeBorderCountyPop:\n",
    "                unitCounties.append(c)\n",
    "    else:\n",
    "        if countyPop[c] < maxInteriorBorderCountyPop and c not in allFusedCounties:\n",
    "            unitCounties.append(c)\n",
    "print(\"We defined a total of\",len(unitCounties),\"unit (but not corner-cluster) counties in the map\")\n",
    "print(\"excluding the cut-out districts and collapsed counties\")        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e0ff719c-59dc-4827-a522-11bd352f7524",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For this state, do we have a lot of populated fragmented VTDs?\n",
      "151 fragmented VTDs out of 4604\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FYI, here are the locations of fragmented VTDs with pop > 3000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"For this state, do we have a lot of populated fragmented VTDs?\")\n",
    "nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "print(len(fragmentedVTDs),\"fragmented VTDs out of\",nVTDs)\n",
    "fragPop = [tractPop[v] for v in fragmentedVTDs]\n",
    "plt.hist(fragPop)\n",
    "plt.show()\n",
    "print(\"FYI, here are the locations of fragmented VTDs with pop > 3000\")\n",
    "for v in fragmentedVTDs:\n",
    "    if tractPop[v] > 3000:\n",
    "        plotPoly(vtdGeom[v])\n",
    "plotPoly(MAP,0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71d771f8-dbe2-48f9-a702-9f66a62d1174",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true,
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\n",
      "I split up 151 fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "looking for surrounds, now working on vtd 0\n",
      "looking for surrounds, now working on vtd 500\n",
      "looking for surrounds, now working on vtd 1000\n",
      "looking for surrounds, now working on vtd 1500\n",
      "looking for surrounds, now working on vtd 2000\n",
      "looking for surrounds, now working on vtd 2500\n",
      "looking for surrounds, now working on vtd 3000\n",
      "looking for surrounds, now working on vtd 3500\n",
      "looking for surrounds, now working on vtd 4000\n",
      "looking for surrounds, now working on vtd 4500\n",
      "After surround checks, we appear to have 4023 building blocks defined. We captured 268 surrounded VTDs\n",
      "working on unit neighbor lists for county 0\n",
      "WARNING - unit 174  = vtd 206 in county 0 has only 1 neighbor= [173] . Optional triage in next block\n",
      "working on unit neighbor lists for county 20\n",
      "working on unit neighbor lists for county 40\n",
      "working on unit neighbor lists for county 60\n",
      "WARNING - unit 1051  = vtd 1545 in county 63 has only 1 neighbor= [1050] . Optional triage in next block\n",
      "WARNING - unit 1058  = vtd 1551 in county 63 has only 1 neighbor= [1057] . Optional triage in next block\n",
      "working on unit neighbor lists for county 80\n",
      "working on unit neighbor lists for county 100\n",
      "All done creating unit lists\n"
     ]
    }
   ],
   "source": [
    "#3/2/24 - split up all multipoly VTDs into fragments, divvy pop by area\n",
    "unitPop, unitCP, unitGeom, nbrUnitGeom, allUnits = list(), list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#These surrounded VTDs don't get transferred to the unit list\n",
    "print(\"Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\")\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(   countyGeom[c] )\n",
    "    nbrUnitGeom.append(countyGeom[c] )\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "\n",
    "nFragmentedVTDs,fragmentedVTDs, coastalFragmentedVTDs = 0, list(), list()  #a prev version treated coastal separately\n",
    "fragVTDgeom, parentVTDno, fragVTDpop = vtdGeom.to_list(), [v for v in range(nVTDs)], tractPop.to_list()  #these lists will expand to include vtd fragments \n",
    "origVTDgeom = vtdGeom.copy() #we create a parallel fragVTDgeom list which grabs the 1st fragment, then append fragments to the total list\n",
    "origVTDpop = tractPop.copy()\n",
    "VTDchildren = [[v] for v in range(nVTDs)]  #the list of all fragment numbers associated with the original VTD, including ones that get surrounded\n",
    "countyFragVTDset = [set(countyTractList[c]) for c in range(nCounties)]\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "            geos, areas = [geo for geo in vtdGeom[v].geoms ], [geo.area for geo in vtdGeom[v].geoms]\n",
    "            for i, geo in enumerate(geos):\n",
    "                if i == 0:\n",
    "                    fragVTDgeom[v] = geo\n",
    "                    fragVTDpop[v] = tractPop[v] * areas[i] / np.sum(areas)  #overwrite, then distribute balance below\n",
    "                else:\n",
    "                    fNo = len(fragVTDgeom)\n",
    "                    fragVTDgeom.append(geo)\n",
    "                    fragVTDpop.append( tractPop[v] * areas[i] / np.sum(areas) )\n",
    "                    parentVTDno.append(v)\n",
    "                    countyFragVTDset[c].add(fNo )\n",
    "                    VTDchildren[v].append(fNo)\n",
    "                    nVTDneighbors.append(0)\n",
    "                    lastVTDneighbor.append(-999)\n",
    "                    \n",
    "print(\"I split up\",nFragmentedVTDs,\"fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "\n",
    "debugV = -7616\n",
    "for kk,V in enumerate(populatedTractList):\n",
    "    if kk%500 == 0:\n",
    "        print(\"looking for surrounds, now working on vtd\",V)\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for v in VTDchildren[V]:\n",
    "            for vv in countyFragVTDset[c].difference({v}) :\n",
    "                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    lastVTDneighbor[v] = vv\n",
    "                    if v == debugV:\n",
    "                        print(\"I just added neighbor\",vv,\"to magicV\",v)\n",
    "                #if nVTDneighbors[v] >= 4:  #Enough to have >=2 even after surrounds.  Will do full neighbor list later\n",
    "                #    break\n",
    "            #if STATE == \"TN\":  #Tennessee has a lot of discontiguous county fragments.  Force the nearest intracounty to be a neighbor\n",
    "            #    if nVTDneighbors[v] == 0:\n",
    "            #        listMinusSelf = list( countyFragVTDset[c].difference({v}) )\n",
    "            #        fragDist = [fragVTDgeom[vvv].distance(fragVTDgeom[v]) for vvv in listMinusSelf ]\n",
    "            #        minIndex = fragDist.index(np.min(fragDist))\n",
    "            #        vv = listMinusSelf[minIndex]\n",
    "            #        nVTDneighbors[v] +=1\n",
    "            #        lastVTDneighbor[v] = vv\n",
    "            #        print(\"I am forcing an intracounty neighbor for VTDfrag\",v,\"of vtd\",V,\"in county\",c,\"to be VTDfrag\",vv)\n",
    "            #        forcedPairList.append([v,vv])\n",
    "            if nVTDneighbors[v] < 4:  #OK if a vtd has only 1 intracounty neighbor IF it touches another county, it's not surrounded\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if fragVTDgeom[v].intersects(countyGeom[cc]):\n",
    "                        if cc not in unitCounties + allFusedCounties:\n",
    "                            for vv in countyFragVTDset[cc] :\n",
    "                                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                                    nVTDneighbors[v] +=1\n",
    "                                    lastVTDneighbor[v] = vv\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                print(\"WARNING. vtd frag\",v,\"in county\",c,\"intersected county\",cc,\"but had no intracounty neighbors\")\n",
    "                                plotPoly(fragVTDgeom[v],2)\n",
    "                                plotCenter(\"iso\",fragVTDgeom[v])\n",
    "                                plotPoly(countyGeom[c])\n",
    "                                plotPoly(countyGeom[cc],0.2)\n",
    "                                plotCenter(cc, countyGeom[cc])\n",
    "                                plt.show()\n",
    "                        else:\n",
    "                            nVTDneighbors[v] +=1\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                if STATE == \"TN\":  #for TN, we tolerate some discontiguous counties\n",
    "                                    print(\"vtd fragment\",v,\"with no neighbors in its county\",countyNo[parentVTDno[v]],\n",
    "                                          \"borders a unit or fused county\",cc)\n",
    "                                else:\n",
    "                                    raise Exception(\"ERROR! Neighborless vtd fragment\",v,\"neighbors a unit or fused county\",cc)                                \n",
    "            if v == debugV:\n",
    "                print(v,\"has\",nVTDneighbors[v],\"neighbors.  its last is\",lastVTDneighbor[v])\n",
    "                \n",
    "for loop in range(3): #to catch surrounds of surrounds\n",
    "    for V in populatedTractList:\n",
    "        c = countyNo[V]\n",
    "        if c not in allFusedCounties and c not in unitCounties: \n",
    "            for v in VTDchildren[V]:\n",
    "                if nVTDneighbors[v] == 1:\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                        for sNo, s in enumerate(surroundedVTDs):\n",
    "                            if surrounders[sNo] == v:\n",
    "                                surrounders[sNo] = vv\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(vv)\n",
    "                    nVTDneighbors[vv] -=1\n",
    "                    nVTDneighbors[v] -=1 #in case this surrounder becomes a later surroundee\n",
    "                    fragVTDpop[vv] += fragVTDpop[v]\n",
    "                    fragVTDpop[v] = 0\n",
    "                    if lastVTDneighbor[vv] == v:  #find another neighbor in case this surrounder is also a surroundee in loop 2\n",
    "                        for vvv in countyFragVTDset[c]:\n",
    "                            if vvv not in [v,vv]:\n",
    "                                if fragVTDgeom[vvv].intersects(fragVTDgeom[vv]):\n",
    "                                    lastVTDneighbor[vv] = vvv\n",
    "                    if lastVTDneighbor[vv] == v:\n",
    "                        print(\"WARNING.  We did not find another neighbor of surrounder\",vv,\"other than surroundee\",v)\n",
    "                    if loop > 0:\n",
    "                        print(\"On loop\",loop+1,\"for county\",c,\" we found that vtd frag\",v,\"now has only 1 neighbor\",vv)\n",
    "if STATE == \"WI\":  #state-specific manual surround enforcement\n",
    "    specialSurrounded = [1610, 1611]\n",
    "    specialSurrounder = 2901\n",
    "    print(\"special for\",STATE,\", I believe that\", specialSurrounded,\"are surrounded by vtd (fragment)\",specialSurrounder,\". Here, let me show you\")\n",
    "    c = countyNo[parentVTDno[specialSurrounder]]\n",
    "    plotPoly(countyGeom[c], 0.5)\n",
    "    for v in specialSurrounded:\n",
    "        plotPoly(fragVTDgeom[v])\n",
    "        plotCenter(v,fragVTDgeom[v])\n",
    "    plotPoly(fragVTDgeom[specialSurrounder],0.2)\n",
    "    plotCenter(specialSurrounder, fragVTDgeom[specialSurrounder], 8)\n",
    "    plt.show()\n",
    "    shouldIcombine = int(input(\"enter 1 to apply the surrounding operation\"))\n",
    "    if shouldIcombine == 1:\n",
    "        for v in specialSurrounded:\n",
    "            vv = specialSurrounder\n",
    "            if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                for sNo, s in enumerate(surroundedVTDs):\n",
    "                    if surrounders[sNo] == v:\n",
    "                        surrounders[sNo] = vv\n",
    "            surroundedVTDs.append(v)\n",
    "            surrounders.append(vv)\n",
    "            nVTDneighbors[vv] -=1\n",
    "            nVTDneighbors[v] = 0 #we are capturing all surroundees (some of whom may touch other surroundees)\n",
    "            fragVTDpop[vv] += fragVTDpop[v]\n",
    "            fragVTDpop[v] = 0\n",
    "\n",
    "\n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] >1:\n",
    "                unitCP.append(fragVTDgeom[v].centroid)\n",
    "                unitGeom.append(fragVTDgeom[v])\n",
    "                unitPop.append(fragVTDpop[v])   #for now, ratio pop by area, not block decomposition\n",
    "                vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "                allUnits.append(v)\n",
    "#for V in populatedTractList:\n",
    "#    c = countyNo[V]\n",
    "#    if c not in allFusedCounties and c not in unitCounties:  \n",
    "#        for v in VTDchildren[V]: \n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] == 1:  #a surrounded VTD, transfer its pop to surrounder unit.  Don't bother with shifting centerpoints\n",
    "                print(\"somehow we missed 1-neighbor vtd frag\",v,\" with last vtd frag nbr\",lastVTDneighbor[v])\n",
    "            if nVTDneighbors[v] == 0 and v not in surroundedVTDs:\n",
    "                print(\"WARNING. unsurrounded vtd\",v,\"had no found neighbors\")\n",
    "\n",
    "for i, L in enumerate(CCBlist):\n",
    "    unitCP.append( CCBcp[i] )\n",
    "    unitPop.append(CCBpop[i])\n",
    "    unitGeom.append(   CCBgeom[i])\n",
    "    nbrUnitGeom.append(CCBgeom[i])\n",
    "    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined. We captured\",len(surroundedVTDs),\"surrounded VTDs\")\n",
    "\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    for v in countyFragVTDset[c]:\n",
    "        if v in allUnits:\n",
    "            countyUnitList[c].append(allUnits.index(v))\n",
    "\n",
    "sketchyList = list()\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for uu in countyUnitList[cc] :\n",
    "                            if countyGeom[c].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu)\n",
    "                                unitNbrs[uu].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:  #non-unit county      \n",
    "            for u in countyUnitList[c] :\n",
    "                for uu in list( set(countyUnitList[c]).difference({u}) ) :\n",
    "                    if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                        unitNbrs[u].append(uu )  #will catch complement later in this county's loop\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if cc not in allFusedCounties and cc not in unitCounties: #see an above block for handling unitCounties\n",
    "                        for uu in countyUnitList[cc]:\n",
    "                            if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu )\n",
    "\n",
    "            for u in countyUnitList[c] :\n",
    "                for i,geo in enumerate(CCBgeom):\n",
    "                    if geo.intersects(unitGeom[u]):\n",
    "                        unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                        unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "                if len(unitNbrs[u]) == 0:\n",
    "                    print(\"ERROR - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has no neighbors\")\n",
    "                if len(unitNbrs[u]) == 1:  #after fragmentation, this unit appears surrounded.  Next block to confirm it has non-intracounty neighbors                       \n",
    "                    print(\"WARNING - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has only 1 neighbor=\",unitNbrs[u],\". Optional triage in next block\")\n",
    "                    sketchyList.append([u,unitNbrs[u][0] ] )\n",
    "\n",
    "CCBunits = CCBlist.copy()                        \n",
    "for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "    for ii in range(i+1,len(CCBgeom) ) :\n",
    "        if geo.intersects(CCBgeom[ii]):\n",
    "            if STATE != \"WA\" or i * ii != 3 :  #In WA, we don't allow ferry connection of Island to Clallam+Jefferson\n",
    "                unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "                unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"All done creating unit lists\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "94741893-6835-45ac-9793-64cbaf4823b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sketchy unit 174 has neighbor list [173, 16, 18, 27, 32, 35]\n",
      "sketchy unit 1051 has neighbor list [1050, 28]\n",
      "sketchy unit 1058 has neighbor list [1057, 22, 28]\n"
     ]
    }
   ],
   "source": [
    "if len(sketchyList) == 0:\n",
    "    print(\"Great! all units appear to have multiple neighbors; no checks needed.\")\n",
    "for L in sketchyList:  #hope that some of these flagged units picked up unit-county or CCB neighbors\n",
    "    print(\"sketchy unit\",L[0], \"has neighbor list\",unitNbrs[L[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cb4277b4-d6ef-4c8c-aa23-6fde227379ff",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8378940d-4387-4188-8ae1-a62010500ecb",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now build the border topology\n",
      "counties and clusters done, now working on (frag) vtd-based units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now build the border topology\")\n",
    "borderUnits, borderType = list(), list()\n",
    "for c in borderCounties:\n",
    "    if c in unitCounties:\n",
    "        borderUnits.append(allUnits.index(c+0.5))\n",
    "        borderType.append(\"county\")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if CCBgeom[i].intersects(MAPexterior):  #should usually be the case, but exception in VA\n",
    "        borderUnits.append(allUnits.index(i+0.25))\n",
    "        borderType.append(\"cluster\")\n",
    "print(\"counties and clusters done, now working on (frag) vtd-based units\")\n",
    "for c in borderCounties:\n",
    "    if c not in unitCounties + allFusedCounties:\n",
    "        for u in countyUnitList[c]:\n",
    "            if unitGeom[u].intersects(MAPexterior):\n",
    "                borderUnits.append(u)\n",
    "                borderType.append(\"vtd\")                \n",
    "if STATE == \"WA\":\n",
    "    print(\"adding a border unit between Island and Jefferson Counties, as these are only ferry-connected\")\n",
    "    borderUnits.append(2647)\n",
    "    borderType.append(\"vtd\")\n",
    "\n",
    "for i,b in enumerate(borderUnits):\n",
    "    plotPoly(unitGeom[b])\n",
    "    if borderType[i] == \"cluster\":\n",
    "        j = int(allUnits[b])\n",
    "        for c in CCBlist[j]:\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "            plotCenter(\"fused\",countyGeom[c], 6)\n",
    "for c in unitCounties:\n",
    "    plotPoly(countyGeom[c],0.4)\n",
    "    plotCenter(\"unit\",countyGeom[c],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "937d923d-9e95-45e9-9aef-77cb4377781d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that the list of borderUnits is contiguous all around\n",
      "number of border units = 152\n"
     ]
    }
   ],
   "source": [
    "print(\"checking that the list of borderUnits is contiguous all around\")\n",
    "print(\"number of border units =\",len(borderUnits))\n",
    "for u in borderUnits:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderUnits).difference({u})),unitNbrs)\n",
    "    if not isUnbroken:\n",
    "        print(\"border is discontig if we skip\",u)\n",
    "        for uu in smallPieceList:\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"n\"+str(uu),unitGeom[uu])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "        print(\"above is with unit numbers; below is VTDfrag nos\")\n",
    "        for uu in smallPieceList:\n",
    "            vv = allUnits[uu]\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"v\"+str(vv),unitGeom[uu],8)\n",
    "        v = allUnits[u]\n",
    "        plotCenter(v,unitGeom[u],8)\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "borderSet = set(borderUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "93603f77-77fa-4453-b54b-5ea07fcb6721",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here, we identify 'border' units that aren't needed to define the map border\n",
      "Bueno! no 'border units' that could be eliminated from the border set\n"
     ]
    }
   ],
   "source": [
    "print(\"here, we identify 'border' units that aren't needed to define the map border\")\n",
    "canBeRemoved, powerNeighbors = set(), set()\n",
    "for u in borderUnits:\n",
    "    uNeighbors = list(borderSet.intersection(set(unitNbrs[u])) )\n",
    "    if len(uNeighbors) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        uu = uNeighbors[0]\n",
    "        otherBorderNeighbors = set(unitNbrs[uu]).intersection(borderSet).difference({u})\n",
    "        if len(otherBorderNeighbors) > 1:  #this neighbor of our 1-border-neighbor border unit makes a border chain without the problem border unit\n",
    "            canBeRemoved.add(u)\n",
    "            powerNeighbors.add(uu)\n",
    "        plotCenter(uu,unitGeom[uu],6)\n",
    "        plotPoly(unitGeom[uu],0.5)\n",
    "        for uuu in set(unitNbrs[uu]).intersection(borderSet).difference({u}):\n",
    "            plotPoly(unitGeom[uuu])\n",
    "            plotCenter(str(uuu)+\"=N of\"+str(uu),unitGeom[uuu])\n",
    "        for uuu in set(unitNbrs[u]).difference(borderSet):\n",
    "                plotCenter(uuu+0.1,unitGeom[uuu],6)\n",
    "                plotPoly(unitGeom[uuu],0.1)\n",
    "        c = countyNo[allUnits[u]]\n",
    "        #plotPoly(countyGeom[c] )\n",
    "        #plotCenter(c, countyGeom[c])\n",
    "        plt.show()\n",
    "if len(canBeRemoved) == 0:\n",
    "    print(\"Bueno! no 'border units' that could be eliminated from the border set\")\n",
    "else:\n",
    "    print(canBeRemoved,\"is the list of 1-neighbor 'border' units that can be eliminated from the border set\")\n",
    "    print(\"... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\")\n",
    "    yesRemove = input(\"enter 1 to remove these from the list of border units\")\n",
    "    if int(yesRemove) == 1:\n",
    "        canRemove = True\n",
    "        for uu in powerNeighbors:\n",
    "            testSet = (borderSet.difference(canBeRemoved)).difference({uu})\n",
    "            if not isContiguous(list(testSet),unitNbrs):\n",
    "                canRemove = False\n",
    "                print(\"We can't complete the border if unit\",uu,\"is not included in the ring\")\n",
    "        if canRemove:\n",
    "            borderSet = borderSet.difference(canBeRemoved)\n",
    "            borderList = list(borderSet)\n",
    "            borderUnits = list(borderSet)\n",
    "            print(\"Success! we removed\",canBeRemoved,\"from the list of borderUnits\")\n",
    "    else:\n",
    "        print(\"Fine, be that way.  Sheesh, I will keep them.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b13c68e3-33ed-48b3-acca-78012ce0bf61",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is the final border set\n"
     ]
    },
    {
     "data": {
      "image/png": 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ktMsRiokeztAhT7FsWSUlxTNJ63EBNluk1WF1WrW1mykq+hIU1b+yamCeDAUl8KiiBObKUFD32KcFOo4Gjmn1erX1vn28Hgx/mQi+7tDsUrcbkvpZHYUQIUGSj3bSo8c01qy9ndlzRpCYcAJDhjyFprmsDqvT2blrOjt3vo7DkYRpGoAZeDT28Wi2eN4+35hdrrR2OY84RE1L63Th5MMV41/bRQghyUd7SU09m6iowewu/ZHNmx+mtGy2rANzGEzDQ1TUYMaN/ezQXtcqEWmdmOw/adFbHacoNkk+rNJU89GFm11iMqBsi9VRCBESJPloR+HhvSjd+FcUxUZYWE+rw+mUDNOHotgP+XX+JhXN38wiOqFu0OE0Yxysuxc8deAItzoaISwlDdztqLY2l/LyeQwc8CBRkQOsDqdTMk0viiI5cbfTHTqc9p7kn0xtxy9WRyKE5ST5aEe1dZsBcDhTLI6k8zINH6okH91Pd+hwmjQAIlNgyyyrIxHCcpJ8tKPc3EeJjz+W+LgJVofSaRmmD0U99GYX0cl1h+ntFQX6Toa1n1odiRCWO6Lk4+GHH0ZRFH7/+983lTU0NHDzzTeTkJBAZGQk06ZNo6io6Ejj7BQ01YVNi5R+B0fANH14vWUyYVt301jz0dUXl4tMAXeN1VEIYbnDTj4WLVrE888/z7Bhw1qV33bbbXz++ee8//77zJ49m/z8fM4777wjDrQzyMy8muKSr1i+4lrWrLmdhQvPYsmSi6moXGJ1aJ2Gotiorl7DunV/sjoUEUxh8f7Hyp3WxtHRyrdCWBwYXbh5SYiDcFjJR01NDZdddhkvvvgicXFxTeWVlZW8/PLL/Pvf/+bEE09k9OjRvPrqq8ybN49ffun6nazS0i5g0MBH8XorqK/fTlTUYAzTw9Klv2Lt2jupqdlodYghr3+/+7HZYvB4y6wORQSTM7A4Y1dudgEYex2UboLlb1sdiRCWOqzk4+abb+aMM87g5JNPblW+ZMkSvF5vq/IBAwaQlZXF/Pnz93kut9tNVVVVq5/OrEePcxk75gPGjPmAgQMfYvSod+jd6xZKy+ayfMXV0pzQBqczidjYsTLTaHfTuDij1sU7G/ecAEMvgB/+Dp5aq6MRwjKH/An/v//9j6VLl/LQQw/tta+wsBCHw0FsbGyr8pSUFAoLC/d5voceeoiYmJimn8zMzEMNKaSpqpPs7JsYOOAB3O5CKiqkCaZNptFi6KXoFoxAUq528eQD4MT/g7oyWPiC1ZEIYZlD+oTfsWMHt956K2+//TYuV/tMHX733XdTWVnZ9LNjx452OW+oiY0dT2REf5Yuu4QVK39DbW2u1SGFLBMjsDaL6DYaO5p2h5FOcdkw4lL48SEo2WB1NEJY4pC+ZixZsoTi4mJGjRrVVKbrOnPmzOHpp59m5syZeDweKioqWtV+FBUVkZqaus9zOp1OnE7n4UXfidhsEYwd+ylFRZ+xNe9pli77FWPHfozLue/fS7dmGsgo8G5GDzS7lG+F4vWg2f39P0zd//fQOP+HagNFA7Xxp/G5bT9lIfp3dOqDsO1n+Ox3cPVXoRunEB3kkJKPk046iVWrWi8JffXVVzNgwADuuusuMjMzsdvtfP/990ybNg2ADRs2sH37diZMkLkvVNVOjx7TiE+YxKJF57BkycWkpkxF08JJTDyJyMj+VocYEvzrrMiHcbdiD/MnDF+38ygnRfMnMqrd35+kMXFpelT3SFhalAVWP6Zx1WNFaVFG67LAMZui86mzuf0rJaMEpv1XWqy83LiyMihpdSj1q0hYeA9JR+3djC1EV3ZIyUdUVBRDhgxpVRYREUFCQkJT+TXXXMPtt99OfHw80dHR3HLLLUyYMIGjjjqq/aLu5JyOREaNfJvNmx+ioPBjfL4atmz9D+PGfi4JCP5ml+ZlTkW3EB4Pd2yAmiLw1PibYRpv9EogEcD09w0xfP4aEcMXeN643Vje4rnubfHo9e8zjT3O06Ks5XkxA7UutNg2AjUyjbUxrcu3RxQR6QvDqdvxr8hs+h8x/Ydigul/boaBz+ViV917DC6aSGrKmRb+AwgRXO3eu+vxxx9HVVWmTZuG2+3m1FNP5dlnn23vy3R64eE9GTbsvwDU1eUx/5eTqK3dLMkHgNR8dE+RSf6fTso0dfixH5lD7yct7fyDfI3J0mWXsWvXO5J8iG7liJOPWbNmtXrucrl45plneOaZZ4701N1GdfUaABrc+WzOfZTy8l+IiRlJTp+7UPfT+9/nq6W84hdczh7YbJFUVa9GUTQS4o9F0zr3ipkmJgoyS6zoXGpq/J1HNe3gO+NXVa+kuno1KZJ4iG6mG4xrC33x8ROJiR7J5s0PY7PFEBk5gB07XiE56VRiY8fsdbxh+Fi67JKmpKUlmy2WoUOeJD7+6GCE3iFMU29e60OITqKo6HMAtmz1//9nt8cd8PiGhnyWL/81kZH96df3nmCEKETIkOQjBNjtcYwZ8wG6Xoei2PH5Kpn701Hsyv8fimonKnIAqto8IqiqegXV1WsYNvQ5bPY4dF8N0dFD0fU6li2/mi1bHu/UyQcYMsmY6HT69LmTmtqNlJbOIjf3MQYM+McBj99dOgtdr2H4sJc6fW2lEIdKko8Q0vgB5HAk0q/fX8jNfZTCwo+x2+NJTDwJ0/Si+2qpqd2IotiIjR2P3R7T9PrS0rnU128nOelUq95CuzBNUyYZE52OoiiUl/uXkejRo+0+H3XeesrNSHTDRzeY3USIViT5CFGZGZeTnnYh1dVrKSz6jMqKJWhaOJotgpjoEQwc8FCrxAOgtGwOYJKefpk1QbcbIzAkUYjOQ9fdGEYD8XHHEBMzYp/H+AydooYq7loxm+8aRoPyMttyV3H7oOODGqsQVpPkI4SpqpOYmJHExIw8qOMzM66ipPhrFi0+m9TUc9BUFympZxMZ0beDI21fpkyvLjohn8+/LlVS8v5rHh9f9TGPleUA2U1lr5YlMrqsmknxUR0coRChQ5KPLiQsLJ2xYz9l0+YHKC2djddbzs5dbzHhqO9wOBKtDu/gmQaKIqNdROdi4l+fJsyV3lRW53Pzed5PrKqqwKGF8WxZDgD/TN/N5Tknku/xcfPabVy0IpdTEqL5S04aOeHts3SFEKFMko8uxuGIZ/CgxwD/0L8FC0+ntja3UyUfpnQ4FZ2QGVgcT1H8H6ubKgu4acUiVulZKMShmgb9te38MTOMqb1PASDD5eCTkTl8UVLJ33LzOX7heu7tk8b1mcmWvQ8hgkGSjy7G56umsnIpPr2WysplAJ0q8QACq9pKnw/RuRiGl++YzNtrVrPLLGGFno2dVJ7t1cCUjFHU+dwkuPYeOq8oCmcmx3JKQjQPbingL5vzGRkVzrjYSAvehRDBIclHF2IYbhYsnEpDw04AFMVOVtZ1hIf3tjiyQyM1H6Iz2mVE8apyPYrPYLhtO39J2cHUjKFkRmcDEGZz4PP5mo73mSaGabY6x509k/igqIwPisol+RBdmiQfXYiu19HQsIv4+GPplf1bduW/w86db1FePp/Ro/6HpoVZHeJB8Q+1lZoP0bnoin+o/Bej+jM6ZtRe+2+cvZCPDQc23Z+A+LT9f/wm1FV3TJBChAhJProQVQ1jQP+/s2Hj3ygrm4vNFk16+sXs2PEqZWU/kZR0ymGf2zRNdL0GXW/AMBrw+iqbljlvXCyriaK0GCqrBNZp8a/u2bRPUVHQUBQ10LlUbdr2esuk5kN0Oiuq6wD4/frtXJQa32rfypp6PjMcxNVWcXFSNAB2wBn436S+rp6y8jJSklNYuXwZkyaODWboQgSdJB9dgGG4WbP2DxQXzyAmZgxDBv8Hmy2SqKjB1NVtYceOV1vNkHo4tuY9xdatT7RTxG1TVUfQriVEexgU6a9Z3FTn5untxZjQIgWHkxsqOLF4C7+e+msA3n//fdasWcPUqVP5YtZMogGPZqOv7iM98TQr3oIQQSPJRxeQn/8BxcUz6N3rNoqKv2TV6ptISjoVmy2a4uKviIwcRFzc+CO6hruhgLCwbPr1vQdVdTUtnqWqLlrWaDTXgrRcSrzxecslxXX/fB6m/9Gk9XZszN4d84QIZcOiwik8YcR+97/33nu47c1zma5Z41+b6YsvvgAgLiKV8tpCAMrzG8jM7LhYhbCaJB9dgGE0oGnh9Or1W7KzbyQ//3127nobgPT0S+iVffMR13yAfw2axMQTj/g8QnRHPp8Pm83/kWsYxl77jR2JxBo9cDt28P1z7+Arn8So0yYFO0whgkKSjy5A0yLQ9TpM00RRNNLTLyY9/WKrwxJCtJCfn09sbCwAS5cu3Wt/Q3IuEVuTsZV8TYQ9HvvMgazf8DX9rjsJNVxWfxFdiyQfnZhpmrjdhVTXrEVRpI+EEMGwYf5cln39BYqqBDpJKyhq4DGwjaKwZclCAHLGHoVpmtTU6tTU1PD43/+KvscQW4AwGvDWfAjA6RnX+QsLIP9vv2C7JInU4QOC9h6F6GiSfHRCpmmQm/sIu/LfwefzD8nrmXU9igxPFaLDbVmykF3r1zDwmOMxTRPTMPyPpoG/S5P/eSM9MLdHvAYNBhimiQJEqf7nXiDdBnGaSWFEJJ66WhZVfs3YmNNooBbVtPHN448w+OxTGX3GOdgc8kVDdH6SfHRCW7c+ybbtL9Iz6zfExIwiMrIfYWFZQbjy3t/WhOhuTNMkY9AQTr/lD0G5ns/jodc7W5n3/ttsX7OS8/70FzSbNMOIzk0mU+hkSkvnsDXvKXr3vo2cnDtJSjo5SIkHSPIhBIG+VcH76LQ5HJxw5XVM+/Pf2bVuNV/851/4PJ6gXV+IjiDJRydiGF42bPwLcXETye55Y3Avrqj+amUhujnTMCxp4swaMowzb/8zecuX8M3zT2LoetBjEKK9SPLRidTXb6O+fjs9s64N6jcvIHA9qfkQwjRNf6dSC/QZPY5Trr+F9T/P4Z37/sjaOT/gaai3JBYhjoQkH52Iy5WOzRbL7t0/WnB1tfUU6kJ0U6ZpULprh2XXH3TsCVx4/0NoNjtvvvAat954J68994pl8QhxOKTDaSdgGB5M04eqhhEZ2Y+6+rygx+CfvVSaXYTw1NdTU7o70PfDmhFmHns4H/v6siD9WFAUvtoGQ/NKGZ2dYEk8QhwqST5CXFHxDNatuwtdr8Nuj8frLWPw4P8EPxBFaVpITojurO+4iWxftcKSxMPj9vDoK5/y5hYFQ03kltExXHLCEE55agGzN0nyIToPST5CmGkabN70ENHRw0lNPYe6ujyiIgeSknJG0GNRUKXmQwjAMHRULfgt1j/+tJT7PlvDDjUeNJiSEMnqXJ0b1ywGr8GCpfmYJ/VFUWW+HxH6JPkIYR5vGQ3ufPr0+SOpqWdZG4xMYCYEEBjtompBu17J7jLuev4rfqyKJkl1cs/4FB5YUMRXpTVNx5waE8Hwcp2ydzcQNjAeW1I4tqQwVEfw4hTiUEjyEcIc9gQKC49m7pylZGTMRtMac4DANM4KgIqi+msmEhN1MrMMFEVDQQVF9W8rKgpa4Pne24oSODawrSiB/TRv19ZslKG2QgCGrgdltIuh6zz77rc8t7wGtxLB5Tkq91x5HttWFPPAgiJeGNGTiafl4IpwYLOr1CwsoPqHHdSvKPGfQFWIv7g/4cOSOjxWIQ6VJB8hTFEUNPU4YCc7d0ZhtxtEROr+JekDA0/8jyYNDTYKCiExKQ8Cy9Kbpt5i+frAEvaBcv9U0M3H7bVvH9sJCbLCphCGrqPZOvajc+Hy9fzp3cVsMeMYGeHlkauPIScrFQBbtH96dS05nMhYV9NrIsf1IHJcD4x6H96SOqpn7aT84804+8SiRciMqCK0SPIR4i6++Fq2bNnCJ598QnV1Nf36HsWpp56KprWuTp05cyYbN25kzOiHOiwWU4baCoHu9XZY8lFRWc2fX/iSr3eHE4ODR09K5PzJrft4aTZ/rYtPAZ9uYNuj/4kaZsOZFY3tvBwKH1lM5VdbiZvWV9Z+EiFFko9OoHfv3txyyy0sXLiQ7777jsTERMaNGxf0OOTDSwj/QnGavX1rEkzT5LVP5/D4vCJqlTDOzzS4/5qzCA9z7XWsw+n/4nH9zHVEzVzPDxeOIsxrYvoMwgYnYot1AqBFOoid2pvyDzehRTuImZzdrjELcSQk+egk7HY7Rx99NGvXrmXXrl1WhyNEt6X72rfmY23uTu54bS7rvNEMcnp59IqjGNR3/+s1paZH89yJ/VmzvoSn88s4472l/ItwctDQy93ETu0NgFHnJXxUMg2bK6hfUyrJhwgpknx0Munp6axcuZL8/HzS0tJa7dtfzYRpmHzwz8XUlLtRbQqaTWXiuTn0Hikd0YQ4VIbPh6od+Udng8fL316dyXtbdMINjb9MCOfKc6agttGZVVEUpkzO4dQTexH27moeWbWTmgtzcCwopXZBAfVrSzG9Oka1FzXCjlHrBcBbXIc9OfyI4xaiPUjy0clMmjSJ7du388ILLxBbVo5qGihOJ7UuF06fzpbzzgPDBMOgyJnNxuRTUOMTqCqpp/fIJOJ7RLDyx50U5VVJ8iHEYfDXfBxZs8t/vlrJf2bvQDFNJsfV8ND1U4mPizmkc6g2jfDsaFgFTped2DN707CpHLNBxzTBluDCV1pP7fwCduq7mf3Um5x0/VmkZvQ4otiFaA+SfHQyERERXHvttfzy/PPk5m4BQMEksUcaaWFhhA0f7h86q6pUbnBQ79UYNjIJVVMYfmImYVEONi4sBOm+IcRh8ff5OLKPzvVbCwHIiXeQMmA4z/+ST5i9iHCHRphdI8xhI8yuMbBHFL2TIlm1s5K5m0tQ8A+xVxX/kgefLPc3wY7vHY/DZceREbXXtRaxmZ8XLsOu2Hj59Vc44YQTGD9+/F6d1oUIJkk+OiGbzcYxN9/MMTffjDc/n9wppxM7cCApd96JEmiLdu8uZ9cff8Cl1zLxvBy+e3UtXzy9AtOEmnK35B5CHCbd5zvimo/fn5DNuue+w5HUj4Vby6j36tR79KZHn+EfWRZm13ji4hH87Yu1FFU1EOG0YZpgmCb4/+O6Y3sR7dp3PM8//zwFBQWceOKJjB8/nu+//55vv/2WZcuWMW7cOAYPHkx4uDTFiOCT5KOTs6elEX/5ryh96WVq58wl86WX+PLljRTnN2DYIzjjkjQM3WDDgkLS+sYSlxpOaq9o+o5LsTp0ITol3edDPcIOp316Z3FW0QxOPa8fQ44/bq/9Xt2gqt7LtW8s5jdvLgHgvFHp/PvCEYd0ncGDB1NQUMDKlSsZOXIkp59+OiNGjODHH39kxowZfPfdt/Tt52bCUaeQnn7MEb0nIQ6FJB9dQPIf/kD06aeTd9HF7P74c/IL+oHiJC3VJHncQHxe/8ykQyal03eMJB1CHAnD58V2hENt7U4X0UnJlOXv3Pd+TSUh0sm7v5nAlt01+HSTXokRh3ydiRMnUldXx7x589i8eTMjR44kLS2NSy65hF8WvERJyQtERpazfsNbhIW9SXz8xCN6X0IcrOCvjiQ6hGvQICImHUfVi881leUXKbx4z/c8+cT7ALy3+X/M2zXPqhCF6BJ0r7ddRrvEp2VQtmvfyUcjh01lQGo0Q9JjiHAe+jVVVWXy5MnYbDYaGhrwer0sWfoWX319AvX1/8Ruj6Jnz2eIjhrG6jW/Y+OmB2hoyD/ctyTEQZOajy4k7aGHqHj3XY7J30LE5OOYWTWXwu98hJdF4k7YxRdVH1K2aTsT0+XbjRCHS/f5cIQdeT+J+LQMtq5Y2g4RHZhpmpimydy571JYdAfR0UUoSg+Sk/7BkCEXoygK7swxbN36JPn571FWNpehQ54mIiKnw2MT3ZckH12IFhVFwrXXsmXFz2z6/FvKw7YSkawyPnUcmOAoPIbBqwewe/taIsen4uofb3XIQnQ6/g6n7VDzkZ7B8m++bLfz7Y+iKFx99dVszv0zuu6mZ8/H6NP77FbzAjkdiQzo/zcy0i9jxcrr+WXBaSQnn07vXrcSEdGnw2IT3ZckH11QzCcNHFU/jIH1vTAVMCtNDExOUSaQWBpLA6U0rC0l4+FjrQ5ViE7HaKfp1ePTMjB0nYqiAhLSM9shsv3LyMigvDwanz6UnD7n7Pe4yMj+TDhqJvkFH7Jt239ZsPAMsrNvolf2b/1D+IVoJ5J8dEHpU4dQ/v5GBt47GdXV/E9smia77v4JgKgTOvbDToiuyudxs27uLJKye6OggKKg2WxodjuazR54tDVt2xqf2+2tjolO8nf+Lsvf2eHJB4BhuDFNX5vHqaqTjPRL6ZE6jbxtz7B16xM01O9gwICHUFW5ZYj2IX9JXZAtKQwA3+76VpMO6ZXupu3oU3oGPS4huoL49ExKtucx6/WXABPTMDFN47DPV11S3H7BHcDu0h8AWLP2D4GkSQUU3qsdwDZfNE7FwK6Y2BUDByYO1cCuJNOgnYdaWIG98FrG5/yGU7Okz5g4cpJ8dEGOHpEoDo26lbtbJR9ajLNpu+7Lr4jIrgPThMxxECfJiBAHY+rv72Lq7+9qVWYaBj6fF93rxfD58Hm96IHn+p7buq9p2zAMeo0cE5S4e/Q4n4KCD2io34mJAfg7or5efS4RSgNRSh0+U8OLDQ82vIFtLwPRFf9sqM/mwkuuCqYmxwYlZtF1SfLRBSl2lajj0qn6fjtqmI3Io9NQHRqeJUuajglb/GtYUu9/MuhsuPANi6IVovNTVBW7w4nd4Wz7YIsMGvhPBg385947Zq/k1t69uS5z/2s96aZJrW5w89ptXLsmj1eUbE5Piu24YEWXJ8lHFxV1YhZGg07Vt9uo+WknEaMTqZ2bD8QRkbAK9ZYNoGjw0XWw4WurwxVCWMTARG1jvQVNUYi2abwxtBdXrNrKHzbsIMlhZ2zMoU98JgTIJGNdlqIqxE7tTeofxhA2NInqOYUYZhwRiRuJ/vUF4IqheOVctm7aQYVX1nYQortyGyZ1+sH1WVEUhScGZtEv3MW5yzZx45o8an16B0couiJJPro4W7yLuHNySJ5SQqL9PuLGlKAl+KtX33/8CT5aE8vbuYMsjlIIYaXPiisO+th4u413R/Thvj5pfLW7kud2lHRcYKLLkmaXbsJxzFmw6G6oap46uUH3//M3+FQqi4tYM/t7xp1zwRGvWyGE6FyGRIWxrqYewzT5efNunHaNpEgnNkVBURQ0FWyKgqooaApoqsIYl4teLifzK2qsDl90QpJ8dBfb50NNIeSctNcuzWbjpVuuAWD+B9M59tKryBg4mJTefTt05kUhhPUiNZV3Csp4p6Cs9Y6DrNBwlOp4hxnYNalIFwdP7izdRcpgiOsFH/waYrPAUwv0A/zTRbuiommorgJg7vTXAEjIyOKqx55tOoVeU4sa5kLRtGBHL4ToID+M7c9uT2DyMQX+8cU6Fm8r447J/UmIdKKbJoZhopsmpukf+aIDumGwoaiazxcVsm5YFcMyYq18G6KTkeSjuwiPh9/MglXvQ3kepQVFQGHT7sbEA2D0GedQUboRtzaPLVueQNNc1K5chvl/s4gcNYGer74a/PiFEB0iK8xJVljzEOHXzxvOSY/NZtGyQt68ZlyrNWD2tK6gii9/yKPBe/iTrInuSerJupOwWBh3HZz6ALGXNtdonP7bOzj+imtJyMgCYMmXn1BVP5fEIQXkF7zH5txHKIj4lsLHvdTN/4WKDz+y6A0IITpalMvOv84fxk+bd/PdugPPvtonKZJIp435uaVBik50FZJ8dFOaw8F1T79Cj5z+zHj6MWa98RKlO7eTOXgY0/78N9LH+xt8Jxz1LSNHvO5/kcf/4N21y6KohRDBMLpnHADXvbGYN+bn7fc4h01lZFYsawsqgxSZ6Cqk2aUbi05K5pJ/PEpFYT7VpaWERUWRmJWNoigULRxATc06Zs0e6j/YVAkLTJCqxcZaFrMQouOFO2zceHwfnpuVy/Ozt3DFhOz9HpsU5WRLSW3wghNdgiQf3ZyiKMT1SCeuR3qr8nFjP6OiYhENDfmEh2cT6RzAxptHARB95lQrQhVCBImmKtx12gCcNpV3Fm4/4LHjsuP5ZNkuNhfXkJMcGaQIRWcnyYfYJ0VRiYsbD4BpmuSecQmoNjB8bJowkT7ffYcjI72NswghOjPDMKnyVLBw53qqPbWU1lazIj+fZUVrya/fhGZrICdqBLYYlRs/KOGzay8jzCHzBIm2SfIh2tSwdiOuYTfjGgbuNR/i2TQTNUKmZBeiqyvwrMDW6+9c833rcs2MRHfVoANr67fg7OEfO/fcEie3T7jEilBFJyPJh2iTa1A/wN/rPfLkS0n5/D+WxiOECI5hvQy+LoXfD3qcCEc40c5IhqelkhblX6JhV2U5yZHR1Ps8XPLlRdSwyeKIRWchyYc4KBsmXwXAsOTXrQ1ECBE0Jh7CbGFcM/bkfe7PiI0HYF35GkrqC0kOTw5meKITk6G2ok2m6Wnaro8rPMCRQoiupN5XT5gt7IDH7K7fzU3f3cSghEFcOfjKIEUmOjup+RBtUxys/uE48owUTowfQ5b0MxWiWziY5OPOOXeimzqPTnq0zWOFaHRINR/PPfccw4YNIzo6mujoaCZMmMBXX33VtD83N5dzzz2XpKQkoqOjufDCCykqKmr3oEVwqYrCS30Xs6zPZ8Skx1sdjhAiSBr0hjYTivKGcnJic0gMSwxSVKIrOKTkIyMjg4cffpglS5awePFiTjzxRM4++2zWrFlDbW0tkydPRlEUfvjhB37++Wc8Hg9nnnkmhiHz/ndmpmniMOyYZjyLa6qtDkcIESQNvgZsqg3TNJvKamvK+fqJO5gz/RHWL5rJLSN+y4qSFcwvmG9hpKKzUcyWf1WHIT4+nkceeYTMzEymTJlCeXk50dHRAFRWVhIXF8c333zDySfvu8PSnqqqqoiJiaGysrLpPMJapmmy6+6fAFg1yc2UKQf3bymE6Nz+74bBXDK7+cujCWh73DG2p9l58w/D8Bk+3jnjnQMuRCe6tkO5fx92nw9d13n//fepra1lwoQJ5ObmoigKTmfz6ogulwtVVfnpp5/2m3y43W7cbner4EVoaflhklyTYWEkQohgOoWB1CRsofbCyZiYYJqYpklUSgY5x53JssvPI73AzY33+ddeWOF9mRHnXmtx1KIzOOTkY9WqVUyYMIGGhgYiIyP5+OOPGTRoEElJSURERHDXXXfx4IMPYpomf/rTn9B1nYKCgv2e76GHHuKvf/3rEb0J0bF0j4d3t/4TgDPHXgsMsDYgIURQ9I3pgyfbRfbvHt7n/j5PPsvaN59BsdtJWrmDyNc/B0k+xEE45OSjf//+LF++nMrKSj744AOuvPJKZs+ezaBBg3j//fe58cYbefLJJ1FVlUsuuYRRo0ahqvvvWnL33Xdz++23Nz2vqqoiMzPz8N6N6BC1lTVgmqAoxA0YZnU4QoiOlvsDfH03lZ/6a6K3HDsEFA1X73Siz54G7jr08nKidm5lyNI1mKZCfb4bPTLqsC63ubiGuZtKyPFt5piBmSiRyRAundu7skNOPhwOBzk5OQCMHj2aRYsW8cQTT/D8888zefJkcnNz2b17NzabjdjYWFJTU+ndu/d+z+d0Ols11YgQFBbBSX1uBky21jlJsjoeIUTHevNcABJOOZ6KX7YRlpOMZ1cplQu2UPnLo83HKSaRfSIwDcAwMaqqMOurUcIOPgn5eNlObn9vBTFmNctd18OPgR1pI2HohTDiUgiLbbe3JkLDEc/zYRhGqz4bAImJ/iFXP/zwA8XFxZx11llHehlhIZcNZkTNQtO8nOocZHU4QoiOZOhNm8lPfUrLOUv10nz0HRswvKA4I3D0HYISFu7vlH7VKSiFm2D1hzD2qoO61PrCKv7w/kouGJ3BraMc8AZsSzuD+F4jCC9ahPbtffDDP2DctTDxVohIaN/3KixzSMnH3XffzZQpU8jKyqK6uprp06cza9YsZs6cCcCrr77KwIEDSUpKYv78+dx6663cdttt9O/fv0OCF8Fh1tXw5IRLOdb8kasjCoFeVockhOgoqgaaA3QPbP4OcpoHC2jxPdCMGkqxc97KbUTs+o47ekTwdmE5M67y14hMLl7PGwd5qW/WFKEAD5w7lOrNPwPQM/9LyP+SNY7hDL5tNSx8ARY8DwtfhGEXwYAzwB4G9nBIGQI2Rzv/AkQwHFLyUVxczBVXXEFBQQExMTEMGzaMmTNncsoppwCwYcMG7r77bsrKysjOzuaee+7htttu65DARfDUhPsnGZqrnMBafRXJTLA4IiFEh7rkf/DWefDWNDj/VRhyHqz6AH74O5TnMXjSbFBjwRXLZeWAs7lG4pvwATy1rYjfZiUfcNjt5uJqnpuVy7kj07FrKvG9RpM//FYqXOl4l79LuF4NUalw0n1w1M2w6EVY8josebX5JDYXZB0Fo6+GgWfBAfoXitByxPN8tDeZ5yP0eH1e3rroCuqdNvqc3pNTf/UPq0MSQnS0mmJ4tK9/+5rv4OVADch5L1JuqAwsz9nrJT/2cfC5Hse/84q4JSuZe/qk7fPUuSU1XPf6YlRV4bPfHk24o/X34F8enUaMt5iBd89t/ULDgMrt/qah+nLYsQDWfQHb50HWRJj2IsTIdABWCco8H6L70Ew4as1yAJKPlyYXIbqFyGR/jcKSV5sTj9P+CcMuJA74w9ZCHs0r5Pe2XSi6m1snnIbLGc5AIExVeXBLAb3CnFyYGo9Nba4B+Xp1ATe+M5tIp4OPbzhlr8QDQPXVY2iu5gJ3NXx1F2z7GeKy4ZjbofckyBgDE26GrXPh4xvgv8fACffAyF/5m2ZEyJI6KtEmRVWJ7llHdM86Yrc9CdMvgryfwB0YgiuE6JpOfaD18zG/btq8NiORWJvG+tiB3DnpXFzO8KZ9N2Ulc3ZyLLdv2MHEBet4ZWcJ725bwdAnb+SPSyYT2e8B6PkXcity97qku74Gm7sCs+WaMj88AGs+gf5ngKcW3jgLvru/+fOn17Fww1zofYI/SXlyJCx+BXRfO/4yRHuS5EO0SdE00idUkH7RQLShZ8DGr+G1M+ChdHjzHKvDE0J0FEcE3LrS3+fi9EdBszftirXbeGJgFl/vruLFnSWtXqYpCv8dnM13Y/oxIjqcP2/Ywt9n/xpi/Ms0pGjjAFhbvK3V65Z8+SLOf6YzylyDL7zFoP7cH2D4xXDag/Drb+DEe+Gnx/0JRqPweLjgVfjtIsg+Fr64HZ49yj/6RtYXCzmSfIg2NXUL2j6fTe5S6HMSpA71lzVUWheYEKLjxfX03/THXQd7dCA9NTGGGzKT+FtuPj+V773o5JCocF4YnE2P0sdQTA8p8cey6spV/HbUdQC8kvt/XPr+P1i0tZS83bWYnvqm18acFBisUF8OZVsgJTDMX1XhuD/AmGvgy9vhjXOgYEXzRRP6+Pt+XD/bH/sHv4ZXTgXd266/FnFkJPkQbTIx+TE8jJVOB/X5SzCrdkFdObhioPfxVocnhLDQPb3TGBcTyQXLc7ln405qfPpex3jrNwCQFJHJt9u+5d5F/uQj1TGUVXXv8quP7+X4R2fxj/zR/HvwhwBo08/H9Hlgxh/9w38HnNn6pGc8Bhe8BlX58Pwk+PS3UF0EgLt0Nbu2vUbRgCEYZz8NOxe2TlCE5aTDqWiTaZr8LqW5CjQ1Ippvz19gYURCiFBhVxXeG96Hl3aW8M+thXy9u5I3h/VmUGRznw1Ni8TQq7h/1K94YvFDTeWFnlUADEiN4dqTRvLR0p28sLKKEuMaHrK/jPehntj1en9zSlRK6wsrCgw+FwZMhcWvwqwHMVd/SEXf4ayI3Yiu+Y+JqvYxUlOwR6cH49chDpIMtRVt8hpeRr05ihFJI1heshyAFye/yFE9jrI2MCFESNle7+aC5bkUuL28P6IPfcJdFDS4ufTjvT8rzut7HnHOOE7ueTJDEoc0lTd4dZZuK2f3og84Nq6MuJFnQ8rgNq9dsutTVq//I4aiE67EMXrMB9QXL2Tplj/Rc0cdvX9d2K7vVexNhtqKdtWYn17Y/0L+76j/4/zPz+e6b67j7dPfZliSLDQnhPDLCnNybFwUbxWUcvayzf5C0yQJUFC5bfTvyYnNYVjSMGKcMfs8h8uuMTEnEXJuOOjrmqbJyg23gwKJiSfRp/cdaGGplLANQ1PQBp3fDu9OtCdJPkSbDNPfU1xRFPrH9+e1017jqq+vospTZXFkQohQ80j/DG7LTmH0/LUAjIiO4PFpCxkY2XHzbiiKgsuVQX39TjZu2EFV5Zcoyhd4vAX07nUbWdk3ddi1xeGR5EO0STf9Hci+WfkacaV5VAS6KUcZpn+mQVWzMDohRChRFIV0l4PCE0YE9brjxn7K4iVP8dNcnTVrqhg3Lofjj3+Z8HCZGDEUSfIh2lRTWwzAj5Ub+LFyQ1N50utng0+HhBy4ZYlV4QkhBIYRxvJliUARLpeTyZOfxWaTW1yokn8Z0aYE08bKrdupUxTWx/ahAQM7JraovlC+Hko3Q+FqSB3S9smEEKKd7d69m9dff53qav9cI+eee54kHiFO/nVEmyoNkwRgV3g2ijONGG8NvcvXEm40NB8UI8PYhBDBt3jxYr567x1sVeUoCanceOvvSU5Otjos0QZJPkSbPJGppE6azfRhvTkxwT98yufzsnDeG8zMz0cfcRn3h8VZHKUQojv6+q3XCC/IA+D4qWdJ4tFJyAynok0ewz/U1t5iamWbzc64467hy+xp2Oyu/b1UCCE6jKHrhAUSD4Blq1cRYlNXif2Q5EO0qTH5aLksdiO3YeLcR7kQQnQ0Q289lfvGwkKe3l5sUTTiUEizi2jT8rIanN/mc8nMXaguDc2motlUIuKcFPSLwqVKDiuECD6bw8H1/32Da597nryMHPIy+uDYWsglPRJIdMjtLZTJXUO0KU3VUAK1H1qUnT7ZsYQ7NMq3VzM1KYYT4qMsjlAI0V1FxsXzvz/fzVXHTyKhpopfz/qYLxcutjos0QZJPkSbUux2ACaPSWfj7Sfy9a/Gce2oTGKcNl4a0oshUeEWRyiE6O6uz0zigqWzANBXrLU2GNEmST5Em7y6f3r1G8f1RAl0Oq336LjsMrOpECI0nH3PTI7xDiDcdBJVn2p1OKIN0igm2uTTA6NdtOZctc6jE+GUPx8hhPUMw2Bt+Ep+cJaRF7ER15AJVock2iA1H6JNXsNf82HTmke11Hl8RDik5kMIYb3fTP8MX81gPsDHyrA8Lh491OqQRBvkq6toU2PNh63FqJZat0649CYXQljMqK3l55V2UMFTegIXDBtNckSC1WGJNsjdQ7Rp9a4KAH7asBaPOxqX3UVZTS1hDg3D8KAo9qa+IEIIEQymaVKVt4iN0/7EzePuYYVDp/fYZP40+XSrQxMHQZIP0SaPeycA939ZApQ0lU9MW8CPs36F3R7HhKN+wG6PtihCIUS3UriG2V9eR0lPHwl/L2XYf57k3Pv/SvrRI6yOTBwkST5Em84fbhBR+yBpPe/DIJwGrxe318ug1PHYfS6273gZXa+V5EMIERz/ncjxQElhHK+Mm8h5zwwmvd8Ii4MSh0KSD3EQTNIiCzlmwAiczpRWe0pK7Gzf8TKq6rQoNiFEd/Ld2iK+qL2f/0TcT5K3nF67wsg5+c9WhyUOkSQf4iAEFmpS9h7dousNAJJ8CCGCYnRGDBuqh/NO/X/ICp/JCVMflD5nnZAMtRVtMk3/UFuFvf8HNwwPIMmHEKJjeQyDkfPW8MWtfwegui4ewz2SpMSUNl4pQpHUfIg2mfhXjlSUvXNVw2hAUWyoqvwpCSE6Tr1uUFVbSYF9I1r5ChLLa1HufdDqsMRhkjuGaFPBjm8A+OHr4zG8LhRUQAM0NGctilNF9/nQbPLnJIToGDF2G6ur3uYpj4rhcLIjDk4fP8bqsMRhkruFaJNeG+/f8CSjKTZ/TYipY+KjrkyntiSS6iElxKb2sDZQIUSXtiL+DOqyFwIwMmwnUQ67xRGJwyXJh2hTuHoMPz4/n1teew9HWOsVbPOWL+HDh/6CdqV8CAghOtY3Py1s2t6a1cvCSMSRkuRDtMkMrO2iqHv3+fD5fADS5CKEaD8FK6FwFfQ9hVqlil8WnIqmRXFx3b/YqZaTrsdjDEi0OkpxBOSOIdq0etZ3gH864z0ZPi8AqiQfQoj28OKJsGtJ09P8kf0hCnS9mh2n3EjP+X8lQokmddhwC4MUR0qG2oo2paZnAlC+bi3lmzZQvWM7dcXFeKqr8NbXA6DZpdlFCNEOjm89YVj81i2tntfmLCbx2qEomty+OjPF3NfXWQtVVVURExNDZWUl0dEyXXcomHfV5cyvLz/gMaev34lqt4NhkHDjDSRed12QohNCdDmVu5j99WNclHwF55V/wbTYVwGIjR3H8GEvYbNFWByg2JdDuX9LXbloU99JJ2I+9STxv/8dhmmge7wYXg+614vu9RJud5ByRhKmz0fxv/6Fe/0Gq0MWQnRmMel8OOxWKCzno9gzGMVs+hluRgx/BU0Lszo60Q4k+RBtciQlE1/XQP/zL0INDz/gsdXffYciTTBCiCNU5fNPboiicJ/5MCvG9pTEowuRRjPRJkX1T6tuGm230JleryQfQogjsq6mnq93VzU9Tw8LIylGRrd0JZJ8iLY1DrENrPFyIJJ8CCGO1LuFZSQ5bDzQNx2A6cN6WxyRaG/S7CLa1rimy0H0TZbkQwhxsAzDR1n5TxQVfY5pGqiKDUWx8d/CiwC4Z9MuTonV6BvhsjhS0d4k+RBtKvaUArDyuAnURNrQ7Sq6XcMI/Jh2G4bdhumwkbmrAK8xAllnUghxIG7Pbn76aTwA4eF9cDgSMU0vZZXLQbmo6bhJtuXAUEtiFB1Hkg/RpvXZNuadoDIyoj823UTx+FA8Xv+j14vq0VFr69EqdfLiderSvQywOmghRGhrUZMaHTWUfv3uBUzmzB3D2+Y0Kokmmip6R9xiXYyiw0jyIdo0u2whXx+lcvO0p0iPTG+1b3nxcr7O+xq7aseu2nlx1YvcOqqvRZEKIToLpzOJ445dRkHhh2za9A8Kiz5BVZtHs8Tg73DasE0H6fLR5UjyIdo0OmU0X+d9TZht72FuH276kK+2fkVqRCoe3UO8K57+cf0tiFII0dnY7dFkZV5NTPQItm9/merqNdQ3bEf1hhNe3h97XTI1nnFwgtWRivYmyYdoU0JYAgCaou21T1M04lxxXDLgEuKccUzpNQVFUYIdohCiE4uJGcnQoU9jmiZ1dTt46ebpZNg1SuqWo8R+wTiOtTpE0c4k+RBtUth/MjEwfiDfbPuGfy/+Nx7Dw9CkoWRGZQYxOiFEV6EoCi5nGr76n8jzLxuFr6ra2qBEh5DkQxw00zRZvmEds79dQUMxxOc4OOa40cy7ZB6PLnqU19e+jkuTIXFCiMNnGgZ6lJ3UXRVk7a4iusGDNz8fe1qa1aGJdiQLy4k2fb34R1a/Vk1Dainhhck4fc19PwwMOD6fF9yPALDkV0twaA6rQhVCdBFLzziNxWmZVEdGMTG7JxNuvdXqkEQbDuX+LTOcijb1NPsS5oskbmdPnL4w3Fod1z9zHON+m0RDryLUWRmctea3/G/ye5J4CCHaxZoLLyE/PR0lOopvKirIy8uzOiTRjiT5EG2yKf4ZS2NOqaMmvJTe54Zh02yMHTKUO/5wCQBpVX3JdPW0MkwhRBdRVFRE7tatAFxyww307NmT999/n+3btxNilfXiMEmfD9Gmxv/ZLzzjNBzTmv9kNiwoZOUPOwDoNz6F6LgDr3grhBAH44MPPmjaTkhI4Pzzz2f69Om88sorxMbGMnHiRMaOHSsj6zoxST5EmxrXk1PV1v+j//JJLjXlbqbcMJTeI5IsiEwI0RXV19ejqiq33347DocDh8PBNddcw5YtW1i1ahUzZsxg586dnHPOOaiqVOB3RpJ8iDaZhr/mQ9kj+agpd5PWN1YSDyFEu2loaKCmpgaAmpoawsLC0DQNTdPo27cvffv2JScnh48++ojU1FQmTpxoccTicEjyIdpk7Cf5iIx30iMnxoqQhBBdlK7rTdv//e9/AbjjjjuIiopqKh82bBj5+fks+vpn+vTIJqWXDMPtbKS+SrSpqeZjj+ZV3Wtgs+8966kQQhyuiIgI7rrrLi655JKmsjlz5ux13KRjjmOa5yi8z+c2fUaJzkOSD9Em0wQU9urc5a71sfanfFbN2knhlkprghNCdDlhYWH079+frKwsAAYNGtRq/+avlrPzgflNz8vf34jh0RGdhzS7iIOyrz7lqX1iKNxaydx3NxLXI4JL7hsf9LiEEF1XUVERADuX5FL12gZsaPjCIKHChYGd2hMjyUxOp/zDTdRt3k3DCIOcM2QdmM5Akg/RNtPcu80FOPeOUQB8++oaqksbgh2VEKKLO/GY46n8Oo/sxQ5qXFAfZeCoNNmd0EDfa48iIs7fD8RwQcVrG7DP9vFV3r/pPWos7ro6Bh49CbtLlnwIRZJ8iDblry0lywYb3lyH5lBR7SqKXUW1qah2DWNnNQkxTjw7q0FTUWwKSuDR/zywrSoyLl8I0SbTNKlftZvMOQo9lAxqRzrpP+0YVNu+ewoULl+HC5WtSRvYsmwxa+f8AMDP777JcZddzeBJJwUzfHEQDin5eO6553juueeaprkdPHgw9913H1OmTAGgsLCQP/7xj3z77bdUV1fTv39/7rnnHqZNm9bugYvgSQYSw22wZvc+9w8GqPVS/PTyA59IAcWm+hMSeyBBsavEnNGbsAHx7Ry1EKIzathcQfWcnbg3luManEDyWX2wxTj3e7xhGNSuK0E1Ypj0h+sZnncKr/zJvw5MXWUFXz/7OL1HjyMsMmq/5xDBd0jJR0ZGBg8//DB9+/bFNE1ef/11zj77bJYtW8bgwYO54oorqKio4LPPPiMxMZHp06dz4YUXsnjxYkaOHNlR70F0sJwRSVTsrCbt7xMxfAZ6g47uMdA9Orpbx/AYRETbUUxANzF1A9NnYOomeI3Ac9Nf5jOgxXb13F14d9VI8iGEwPTq7H5pFQDRp/Yk+oSsAx6/e/VWGt7aSQIp1A33kfvFp3z61kt7Hbfiw3c56sprOyRmcXgOKfk488wzWz1/4IEHeO655/jll18YPHgw8+bN47nnnmPcuHEA/N///R+PP/44S5YskeSjMwuMdlFVFdWhYnO0X2tdzc+7UJwyXFcIAYpdI2Zqb6pn7aDq+x2oDo2IiWn7ba5tqPCPstNNnb6XHs+rF50NCozpO5ij7vo/dv74PR98/C4zN26h9JNPGDpqFKZp0qNHDxwOWQTTSod9F9F1nffff5/a2lomTJgAwMSJE3n33Xc544wziI2N5b333qOhoYHjjz++veIVVmgca9vepzVMTI+B6pDkQwjhF3VMOhHjUqn8aisVn2+hfkM58ef3RYtu3fRSua2A8h+3EkciVfYyPLt3U64YRKMw6R//BKDPWefQ6+f5rLU7WL1hA4uWLwcgLS2NK6+8Eqdz/805omMdcvKxatUqJkyYQENDA5GRkXz88cdNY7Dfe+89LrroIhISErDZbISHh/Pxxx+Tk5Oz3/O53W7cbnfT86qqqsN4G6IjmexzsMuRn9frXzRGccp0M0KIZqpDI+7sHMIGxFP2wUaK/rOUuPP6EjYkkZpdpeS9P5/I/HDCiaB6QD0DLzuTj6+4ENUwGHfq2U3nKS8vZ21YGAC33XYbZWVllJWV8dFHH/Hkk09yzjnn0LdvX6veZrd2yMlH//79Wb58OZWVlXzwwQdceeWVzJ49m0GDBnHvvfdSUVHBd999R2JiIp988gkXXnghc+fOZejQofs830MPPcRf//rXI34jogN10OSBZmBSIEVqPoQQ++DqH0/K70dT8dEmSt9a11QeSwwVKRX0ufp4wuKjqF+/gR2Gh+gGD8Ou+U3zCczmDy8VSE1NJTU1lbS0NL744gveffddrrjiiqbJzETwKKZpHtGt5eSTT6ZPnz7ceeed5OTksHr1agYPHtxqf05OTtMc/XvaV81HZmYmlZWVREdHH0loop1Uz91F1bd5pP/t6HY9r3d3PUWPLibxuqG4+sS267mFEF2DoevMefs1SmdvpF/sWHAqpP5qJEmDeuPzeNi6fDEJaZm8eseNYJpcddMfSWjR1L/wzTeZkZvLiak9OO6G65vKvV4vb731FoWFhZx22mkoikJRURG5ubn06tWLyZMno2nyxehQVFVVERMTc1D37yPuOWgYBm63m7q6OoC9ljfWNA3DMPb7eqfTKe1uIc5XWo/p2f+/4eEyG3wAqC6ZbkYIsbe6qkq++M8/2bluNcdffg1x2X2Y/+E7rHt/MSYmVSXFVJUUA2B3Ohm2Lo/iG26katAg0v75MM6+fckYOhRyc/mhsIDcv/yFqwM17Xa7nUsuuYR3332XTz/9FIDo6GiqqqooLi7G6/Vy1llnWfbeu7pD+tS/++67mTJlCllZWVRXVzN9+nRmzZrFzJkzGTBgADk5OVx//fU8+uijJCQk8Mknn/Dtt9/yxRdfdFT8IghqVu1GAfLumoMBmCgYir81xlAARSE6ORxbmM0/wZhNRdEUsKlNk40pmgqNk48F9ukV/hovNUySDyFEa+vm/siMpx8DIHv4KOqrq5gz/VWKt+bSd/zRKKpKXGoavUaNpXjrFkaeNhW1sIjaOXMoefIpan7+GWffvqSNGMEfMzJ45OmnMT2eVtdwuVxceeWVNDQ0YJomc+bMYc2aNVRVVZGdnW3Bu+4+DulTv7i4mCuuuIKCggJiYmIYNmwYM2fO5JRTTgFgxowZ/OlPf+LMM8+kpqaGnJwcXn/9dU4//fQOCV4ER/noFIq+3UbW0ET/fB16YA4P3T/nR0VhLWEuDVeMA1P3z+FheAyo8zU9p3Guj8Bj43Mt1okWZbf6LQohQszWFUubtou2bKZ05w6c4eEMOeEUTr725lbH9h3rH3FJdAyufv0oe+NNfAUFmD4fis2GMzYWgHBl787tHreHn79fyuLl86n3+ifHvPTSS0lNTe2w9yYOMfl4+eWXD7i/b9++fPjhh0cUkAg9uk0jz1Q45ddD9tpXXdbAG3+eR89jM4gfnGBBdEKIruj0397BaTf9HlU99H4XalgYZa+/gdHgpsdf70cBwt1utigKaz//nEFnnkldXR3vvfsBedu2AGB3xzF2wKmcccmEfZ5TN0zyK+rJiAuTZSLagYxxFG0yDGO/ayp4G/wjVuzSb0MI0c4OJ/EAyHz5ZeyZmVR99RVGfT2azca1v/418brORwsW8Mlrr/H0U083JR5HDTuBk8ZPZediN5Ul9Xudb01+JZMfn82x//qR695YzPbSuiN6X0KSD3EQdJ+Jqu070/e4/Z1G7TJLqRAiRDgy0kn9v3swqqrYMHIU3uJi4vv25YJjjiGxpITleXnY7DYiqvqQWHgsOT0HMuq0noRFOZg9fT2G3tzBfsH8Rbx+1+/ZXVDA388ezJr8Kk5+fDb//mYDutFB8xB0A/J1VbTJ0A00rY2aD0k+hBAWc2/ejGK3U798ObWLFjWVe7bmYYuNpfiPd3Ic0OPNN4gbO5bywlqm37+AWW+v54oHJzLx/F7MfGEd/735VXoOKsPn8bB50XxSgDuOSuDyCdlMG53BA1+u48kfNnP8gGRGZcVZ9n47M0k+RJuMA9R8eN3+5GPN3F1ExjlRNRXNpqLZFTRNxe7USOsXi80uyYkQouPUr1hB3kUXtyqz98wi7YEHCB8zxl9gsxE5bhxxY8cCEJcawZjTs1k8I4+VP+wgd+l2ANw1ayjZ1kBYVDQ5k05l8+yZxEf6p4QId9i4YVIf3l6wnce/3ciVE7IZlhlDcpQreG+2C5DkQ7RJ1439Jh9R8S7Couysmr0L0zDRfcZeM6KecPkABh2dFoRIhRDdla+8HIDkP/6B8NGjCRsxotX+3c89Bz4ftfPmtSpfPCMPgOXf7cAwoOfgAjb8tJEBR1/OUeddxIZNeWyePbPVbKmZ8eFcflRP3vxlG3M37UZRoE9SJI9dMJzhmbEd+Ta7DEk+RJtM3dxvh9PopDCOvbAfKKBpqj9JUQDTn7R8/fzq/SYuQgjRbnR/LWzMeedhi9u7KaT01dcASH/8363KJ13an9nTN6DZVM6+ZTiq0osNP72DaQbWngpMnLnnXOB/P2cId57Wn4o6Lwu2lvH4txu5+rVFPH/5aMZmx7fzm+t6JPkQbTIME1XddwKxdm4+8z7afMDXR0TLDLZCiI5lBpKP7VdcgRYTC5oWmNzQhuJwYFRVkfynu4ieMqXV64Ycl05iRiRR8S4iYp3s2rATgIwBgWVCAh995j4WuYpy2Yly2cmMD+ekAclc/+YSLnp+PpeN78ktJ+aQHC1NMfsjyYdok6Hvv89HfbWH6EQXF90zDl03MHR/00vjIybE94gIcsRCiO4mfNQoYi+5GLO+AdPQ/RMZGjr4fBgeDxHHHkvExIn7fG1q75im7R59+xGVmMQvH79Hap9+KIHsw2xjZEtchIPp143n5Z+28uysXD5cupM/ntqfq4/u1X5vsguR5EO0yTD2n3y467y4Iuw4ZIp0IYSFbImJ9PjLX474PKqqccq1N/P54w/z+eMPMeyiawJ72h5Wa9NUrp/Uh4vHZvGvmev56+drGZsdz5D0mDZf293IHUO0ad3PqzG82/jksdXYnS4cYU6cYU4cYS4KNpdjczgo2Z6HzeHw/9ibHxVVppIRQnQuvUaO4czb/sRHD9/P7oICAGasKuSHmmWAvyVGURRyVv1M5qYVmJqGqSj+PYq/rmQsEFtax+xZ4Qy57ASr3krIkuRDtMmmLqOufhW5C1Vg36vbvvHHfb9Ws9mwOZ1kDx/N1Fvv7LgghRCiHfUaOYYTr76e3KWLKdRd1IYnUlnVgGkG6kBMmPLTDDILt7CtRw6KYaBgBnqmmsTW6WT56jHqCy1+J6FJkg/RpsyBsdRXD+eCex/A0HW87gYaat3UV9fhrm3AGaZgGF50rwefJ/DTtO1m04J5FG3ZZPXbEEKIQzLytDMZedqZ+92f92MUjmOmcdo//tGqfP6D77Nou3+tq5z6SL5/fS3lhbUMODGZIWN7dmjMnYUkH6JNJkBgISVV03CGR+AMjyAm6eCGk1UUFlBXVdlxAQohhAVM02y1yJxpmqDrLN3evMhmZY2CWldH0dZqfvnoZybEZDKt3zQrwg0pknyItu3xP9ih0n1ebA5HOwYkhBAhwDRB8fdrW/jYJyxb7yCsYTdEZBDmq+SyR07GGRcFwD//+Sau3ZHcP/9+chxxDM8+0crILSfJh2jbnrPr7MFdV8f0/7sDT0M9qqoSnZTM2LOmoWo2NE2jancJml2SDyFEF2MYoCrousGiTdGgQXVEBtE1O7jovxfhiGye50NFJcIRRowBH39+DcPjRkPPiZB1FKSPAVv3+oyU5EO0yeTANR815aWU7drB4Eknk7tkATvXrmbn2tWtjskZe1RHhymEEEHVsGYNDWvWoAwdB/gTjZEToonPOZEdG6swzSpyK3Kp9lRj2x6LJ6aMShWiDAMML8x9DDw1EN8HLv8Y4rpPfxBJPkSbNi2Yd8D9hs8HwPDJUzj1xlupr6pE130YPh1D92HoBlGJicEIVQghgq78njtQj/sPhmpn2fwqmF+1xxE2HNiocFUDEJN9HJz9Jug+KFgOb54Li16Eyf/Y69xdlSQfok2qZsPQffvdr3u9AGg2O4qiEB4TG6TIhBDCOgNWr8KorQVVJQcF0+bCpHk21E82f8Ijix/httG/Z2rvqTwz41Fww9QJd/lPoNkgdSj4GiA63bo3YgFJPkSb6tMHoe5Yyz2XX4ndbsNUNVA1UFUUVUMzvIQDD83cBLFV2FQFu03FoanYNQW7puKwqdg1FadNxWnXcGoqTrv/ucOm4rRp/n02LfDcv9+hBY63qdhU5Yg6vgohRHtSbDa0GP/spdo+9g9M64fHVs+QtEHERkfToDfgNE1Sk4c0H+SuAd0DMZnBCTpESPIh2rQufjhmhULvBBd2DUzdh6HrmLqOaejohp3yHkMpNiPwltfjNQy8uoFPN/Ho/m2vz8Tt0/H4jEBZ21MV70lVINxhI9yhEem0cd+Zgzi+f3IHvGMhhDhyDtXfidSu2gGIc8YQ4ylufZDu9j96aoIZmuUk+RBtis3uR2liT/52Xft1GtUNE4/PaEpI3IHtBq8/OXF7/c/dgX0en0GDV6fBq1Pr1nl21mbW5FdJ8iGECFmNNbWNK+KW1JWQYuxRexuRDMmD4Kf/QL9TISwuyFFaQ5IPYQlNVQhzaIQ59lVZ2bYX5uTish/ea4UQoqN4dQO75p/7o3FF3M2luxiSOIQiVcVr7tF/TrPBBa/BK6fC62fB5Z9ARAJdnSQfolNy+wycNlm0TggROv72+Vpe+Xkrx/ZNJCnKyYrCdRAD9/7yB/4+71941HKw7+O2m9QfrvrSn3x8eA1c8UnQYw82ST5Ep+PTDXyGKcmHECKk9EwIB2Dupt2BknAio1UUxcCj+vt6/K6sguWfP0vSoGNxhccQ7TCwf/5biEyG2EzImxuYvKxrf75J8iE6HbfPv7KuU5pdhBAhZGRWLADvXHcUL8zJZVBaNFcePZenFnzAyb3HEjf/XYZVPgVL7oYle7w4Yxx4auH0R7t84gGSfIhOqCn5kJoPIUQI8QQ+mxIjHbx69bim8r+f9Gv/RvYQVnw/iPriLRiRqWQue5RMs4CNRjr9rv3WipAtI8mHaFOozazh9umAJB9CiNDSmHx8snwXPeMjQPF/fjaOelEAJf44lITjUFDIixzF+m0FfL2xis8r60mJCbMu+CCT5EN0Om5vY82HNLsIIUJHQqQTTVV45sfcgzja5DLnUuyKwelOWLDgF86afEKHxxgqJPkQB6WNhW2DqrnPh9R8CCFCR//UKDY/MAXThMaPTNP0z/LhLzObPku9Xi+P/Wsxp5w6hZLiIlYvns8JE8YQFRVlVfhBJZ/eotORZhchRKhSFAVVVdACPzZNbVpiwmnTcNn9P6rp/xyLj43m1MmnoGkac+fOtTj64JFPb9HpNHc4lWYXIUTnZAaqQBRFISwsjPHjx7NkyRJKSkosjiw4JPkQnU5znw/58xVCdE4tkw+Ao48+mtjYWD788EO8gZXCuzL59BadTlOzi/T5EEJ0UnsmH3a7nfPPP5/du3fzwQcf4PP5DvTyTk8+vUWbQm0Ve2l2EUJ0VvPmzeOJJ55gxowZQHPyAdCjRw8uvPBCcnNzmT59epeuAZHkQ3Q60uFUCNFZffPNN5SXl9PQ0EBOTg4pKSmt9vfr14/LLruMvLw8fv75Z4ui7Hgy1FZ0OtLnQwjRWfXr14/c3FyysrJQFIWPfvyI3fW7URU1MCmZgqIoGIbBrFmzGDdhHOHOcKvDbneSfIhOx+0zcNjUVtWVQgjRGfTt25eioiKWL18OQEldCaZp+j/PWsyn5MSJR/XwzeZvOGfwOZbE2pEk+RCdjtunS62HEKJTGjt2LGPHjm16ftL7JzGt7zRuGnHTXsdeNuMy6ovru2TyIZ/gotNxew3pbCqE6BJ0Q0fZzwpa0Y5oPIYnyBEFh9R8iDbtCFP4xamS/eki7Cg4FHAoCk5VxaWqRGgqIxU7aXYbDk3FGZjJz2FrnNXP/+hoMctfY3nTvsB+m9Z2Puz2GVLzIYToEkobSnl1zavcOOLGVuW6obOiZAWXD7rcosg6liQfok1RmVEYldX0MjQadAO3YeIxDWpNE5/po86usWlXNRFbavD4DNw+A59xeIvBaKrSIklRWyQwgYRFU9lVUS9zfAghugTFhAmxY8gv3EpKchaaqlHrreWH7T9Q7almTMoYq0PsEJJ8iDa5nBrHxEbywcicfe4fPW8NF07sxV2/6tFUZhgmHt3A7TVw63pTUuJp/Ans87TY17i/5XFun77H8QZJUU7GZscF6+0LIUSH2LluNVd+1RPYzjtv3EKt08e8syC/Nh8TkxFJIxiZPNLqMDuEJB+iTSYHnmis3jAI36O5RFUVXKp/ASWwd2h8QgjRGTkjIls9j3DbOCVzEr3jcxicOJic2Bz/ENwuSJIP0SbTZD/dofzKvDphB9FXQwghRLNoVDIr3OyIdQIw7c9/I3v4KIujCg5JPkSbTMz99sYu8/rXH9DNw+vjcSTKvD5m7q5EAeyKgk1VsCmKf7vxMVDmfw42dY/9gWMcioI9sE+V+UOEEEGw9eF5TBx5HwBar1306CaJB0jyIQ6Cyf5rPmoCU50PiAgLWjyN3iko4++5+e1+XpsCdkXFEUhG9ny0qwpJDjsvDc7GJTU+QojDVB/eg8aGl7ABPQ54bFcjyYc4KHtWBpS7vaworqZC18Fr4FCDX1tQp+ukOuwsnjAIr2mimyZe08RnmngNM1BGqzJf4zFG87E+08QT2Odp8VqP4d/2mEbg0f88r97Dd6VVlHh9ZGqOoL9vIUQn56lDXzuDeTXxgE6CLY+LVzwFY7+H8HirowsKST5Em/ZsUXljxU7u/3QNRp2/ycUJVPfPgtjIvV/cgTyGiUMNNK0csFdK+/q+tIrvy6qwSeuMEOJwPNiDal8P4FkADNMGZVvY8t8LebzHI/RPieSm43NQLfhSFyySfIg2tWx2eXP1Lu57ZwVqmMbNZw+kqtbLm99tJs0W/D8lj2HitOB/Tl8gG7NJ3xAhxEHaUFhNRZ2HGasK6BV+NVfVvcqNKdMw0NDwApBauZL1eimfr8jn2L5JDM+MtTboDiTJh2iTicmqXZWcs3Yxy1cXY4t1sPD3xxPvsrM4r4w3v9tsyXTnHtO0pLmnMfnQJPkQQrShsLKBXRV1nP/f+S1qkU+hfNiJjC37nPjjfkPBxiXEhDvpO+ZkrthicP9na8iIC34/umCS5EO0yTBNquYVstxnkjMggTfPH0m8yz93h8fnX97eYcF05x7DwG7BGPjG5MMuyYcQYj90w+T7dUX85s0lTWVPXzqSQT2iSY1xEe6wAWcBMGhY80Jzs79axKisWBIincEOOagk+RBt+nZrKU6fyXHj03nj3BGt9rl165IPt0XNLnrg24vUfAgh9mV+bik3vLWEynp/c8o9pw/k6JxEBvaIQmnjc2NIegwvzd1KvUcnzNF1F9CUcYKiTc75JQDcdnTvvfY11nx0x2YX6XAqhNjTR0t3csmLv9Dg1bloTCZL/u9krjuuN4PSottMPADOGZFOjdvHZyt2BSFa60jNhzhoI5OjAdhZXseT32/CadN4f8kOwJqaD69h4rCw2UU6nAoh9vTuIv9n4q0n9+Wm4/e9HtaBZCdGMHVYD/719QZOG9yDmPCuuTyFJB+iTaOSV7CiZAjD7nsXu2ZQWh/dan//lCjC7MGv+XAbBk7VguTDMFFAZkIVQrTy2s9b2bq7lrNHpB1W4tHovqmDOOmx2TwzazN/Pn1gO0YYOiT5EG06p+8s+sRsJSr2ONxeH9tLVpMeXcs/fvVvAGwWzfLpMUyiLGj78Jmm1HoIIQAoqKznrV+2UevWeW1eHgAnDUw5onMmR7u4aGwm7yzczhUTepIRF94OkYYWST5Em4b37MWwLJ0Rwy+nvn4H8+b/g5TkqZYlHY2s6vOhm9LkIkRX9MpPW8mvqEdTFVRVQVX8NZwKoCgKigIK/nJF8Zct217Od+uK6Z8SxYjMWO4/azAj2mF+jltO7MuMVQXc/u4K3rp2vCVN2x1Jkg/RJgUFE38/B12vByAj8worQwICk4xZ1OdDOpsK0bV4dYO/fbGWpCgnkU4bumFimCamCabp/wRsek6gzPSXjesVz3vXT2jXeGLC7fzn4pFc9tIvXPj8fJ66ZCSZ8V2nBkSSD9Gm8opKfL6FfP31ZFBM7Hb4+adFTJkyEtWCPheNPIaB3aLRLlLzIUTXdOep/blgTKbVYQA0JTW/nb6MM56cyxe3HEtWQtdIQLpWPY7oEEuXxFBQ0BevL4z6eh+lpeksWbIDr9draVzWNbuYMseHEF1M4//R5gGPCr6RWXF8+btjiHDaePrHTVaH024k+RBtUpQB5O86kTOnfsrZZ33PurUnYRh25s+fb2lcbsPEaUES4JWaDyG6nKbRa6GWfQCx4Q5G94xjc3FNq/Il28pYnFfG5uJqlmwr49PlnWduEGl2EW2KTk4hv7CQp775AZvdTtK4iRQv+JmVBUXUllRgUxQ0RcGm+DtiNv60LNMUBbuioLU4Zq/9qoIKBzURDwTm+bCg2Uc3oYv1/RKi26r36CzdXt703AzB7MM0TRbnlXPGsB5NZZV1XqY9t/cXwKQoJxP7JAYzvMNySMnHc889x3PPPUdeXh4AgwcP5r777mPKlCnk5eXRq1evfb7uvffe44ILLjjiYIU1VodFozXk4Z4/F615ZSS+8KqsXJ3X7tdrmZDYWiQs9j3KSrxey2Y4lZoPIUJbfkU9q3ZVoioKmkrg0f8ZoiiBkSyqwuvz8vhiZUHT66JdoTep15bdtRRWNTCmZ1xTWb1XB2BkViw3TOpDmF3jL5+t4YEv1/H5b49BteCz8VAcUvKRkZHBww8/TN++fTFNk9dff52zzz6bZcuWMWDAAAoKClod/8ILL/DII48wZcqUdg1aBFdV30HU9BrA/0b0wafreHUDt8/HHxwOfKaJ1zTRTf9NWTdNfKaJz6R529hHWeA13lavaT5P47m8+3hN4/YJJpyZFBv034ckH0KEvvs+Xc1364oP6tj02DD+95ujUBT/dqhJjw0jLcbFfZ+tobTWwzkj00mNcXH3lAE89u1GbnlnGb85tjf/nDaMC5+fz18/X8Pdpw/EZcHkjwdLMU3ziOqY4uPjeeSRR7jmmmv22jdy5EhGjRrFyy+/fNDnq6qqIiYmhsrKSqKjo9t+gehw167eSo3P4H8j+lgdSki4d9NO5pTXMHvcAKtDEULsx7nP/kxGXDj3TR2EYfqHzepG8/BYw6RpOG1ChCPkV5HNr6jn4a/W89mKfFx2lbOGp3HbKf1w2TRe/XkrT/24mRsm9SElysmDM9aTERfGk5eMZEh6TNBiPJT792H3+dB1nffff5/a2lomTNh7fPOSJUtYvnw5zzzzzAHP43a7cbvdTc+rqqoONyTRQUKvBdRaXlMWlRMiVPl0g1+9vIDVuyoZmRlHUlRoJxUHKy3Wn0zcNWUAnyzbxas/b+W7dcW8dOUYbp/cn+/WFbOjrI67ThvAMX0T+c2bS7j/szV8cONEq0Pfp0NOPlatWsWECRNoaGggMjKSjz/+mEGDBu113Msvv8zAgQOZOPHAb/yhhx7ir3/966GGIYRlFGBNTQM9Z69ApblPiqrQ1CdFpbnfihYob3ps8Zoom8ZTA7OItUvfbyGO1Obiam57dwWrdlVy3qh0rpjQ0+qQ2l16bBg3n5DDpeOyuO6NxVz64i+c0D+ZtQVVXD/Jv/J4TnIUV0/M5v7P1+LTjabZqA3D351WC4H+IIf8ide/f3+WL19OZWUlH3zwAVdeeSWzZ89ulYDU19czffp07r333jbPd/fdd3P77bc3Pa+qqiIzMzQmeBHNpItDs5uykukf4UIP9EvRA/1SdBN09lFmmoFyWr2mxOPj29Iqtjd4JPkQ4gh9s6aQh79az5bdtVw2Pos/TRlAVAh2Hm0vcREO3rp2PP/8ej3zc0u5YVIfzhqe1rQ/Iy4c3TCZsboQp03lh3XF/LChmAaPzp1TBnD5UdYmZof8iedwOMjJ8a/WN3r0aBYtWsQTTzzB888/33TMBx98QF1dHVdc0fYU3E6nE6eza1SLie4h0+XgqvQjH8q2pLKW78uqsEtmJ8QReWnuFl7+aSsen8GfTx/Ab47rHv3TXHaNv5w5eJ/7js5JZFRWLL97ZxkAfZIiOGdEGmW1Xu79ZDX9kiMZ3zshmOG2csRftwzDaNVnA/xNLmeddRZJSUlHenohuixPoK+3FcOFhehK3l+8E4dN5daT+nLxuCyrwwkJDpvKBzdMZFNxDS67Ss+ECMDf9PL16gKWbC/vPMnH3XffzZQpU8jKyqK6uprp06cza9YsZs6c2XTM5s2bmTNnDjNmzGj3YIXoSrxGY/IhM5YJcThM0+Thr9azs7yOS8dnSeKxB1VV6J8a1aqstNZDrUenZ3yERVH5HVLyUVxczBVXXEFBQQExMTEMGzaMmTNncsoppzQd88orr5CRkcHkyZPbPVghuhK3YQDgkGYXIQ6Z26dz90er+GjpLoZnxnLq4FSrQ+oU5mwsAWB0iwnLrHBIycfBzNfx4IMP8uCDDx52QEJ0F95As4sVK/MK0dkt2FLGR0v9a5k8dfHILrPaa0f7Zm0hI7NiSY1xWRqHdLEXbTqyaejE/ngam12k5qNTq/ZUs7N6J6qiYlNtqIqKpmhoqoamaM3PFQ1VVZvKGn8an4tDkx7XPBOpJB4Hx6cbzNtcynXH9bY6FEk+RNsMTFTkBtnevNLhtEv409w/MWfnnCM+j6ZoKIrSKmHZV5KiKRomJj2je/L8Kc9328SlT1Jk07ZXN7Br3fP3cCiW7aig2u3j6BzrF56T5EO0yUTm+egIjTUfMtS2c6tyVzEpYxK/GfYbDNPAZ/gwTAPd1NFN3b9t6K2eN/4cyvOW21/kfsEvBb+gm3q3TT50o7lKtqCiQWo/DsKzP26mV2IEwzOCN+X6/kjyIQ6K3B7bn8c0sQdW2BSdl8/wkRiWyLCkYUG7Zkp4Cg8seACb0n0/wjVV4b6pg/jbF2s57pEfeei8oVwio132yacbrCuoZtbGEh46d2jTjKdW6r5/uUJYzGsY0tm0C9BNHZsa3I9Sj+7BqTm7feL662N6MXtjCbM3lnD3R6sk+diDYZg89NU6Pl6Wz+4aN8lRTqa2mAXVSpJ8CGERj2Hi7OY3j67Aa3jRlOAuXe7W3XgNL//45R9oioZNtaGpGjbFhk210XdHD8ZEjPDHZRL48a/oimFiT4vEkRmJ6rShODWUTpwEv/7rcWT/6UurwwhJi7eV8+LcrZw/OoOpw3owLCOWSGdo3PZDIwoR8mTAS/szgXKfTvqs5TgUlecH92RyovVtsQCmz4dn61bQNBSbDUXTwGZHsfmfo9n8NyxVRXF272/gVtR8DEsaxqCEQawsWYnP9OEz/D+6oVNdWcl7mx6h2rETm93m77ClACgoCuhVnr3Op0baUSPs/n9HTQFVCfz70lTmf66AoqC0PEbBv91YpgQenRpRkzJQHcFLzM5++ic+/e0xQbteqGvw6gD8/uS+ZMSFVp8YST5Em7rvbaVjXdojgXi7DZ9p8qeNO9nZsPdNwSplr79B8SOPHPwLbDYUu92fqAR+sNtQbIGyFvtalTfus9v852hV7t/XqtweOEfTOe1NZfasLMIG73udi47kM3xoanBrPsamjuXt09/e577NW9bBpt1Unx3O4NGj99pv1Hnx7q7HbNAxGnzoVR70Cre/ZsQwwTDBoGl7z0d0A8PbsowW+0xM08T0GuhlDbj6xODsHdvBvw2Ye+cJHPuvH1mxs5LNxTXkJEe2/aJuIC3WPxx5xqoCrju2d0h9SZDkQwiLJDhsXJaWgG6a3LVxJ64Q6ATWSK+owJaSQvpjj2L6dEzdBz4fpq5jen2g+/Ds2EntTz8RNXkyaKp/v9eL6fVh+nyYPm+grPF5y7Lm44yGBswaL7Q6LnCMbx/lPh94vf7HFpPQaLGx9PtlflB/Tw8ueJAd1TtCquNnfXUtLsDh2veCnWq4HWdWx6726i2po+ixJR16jZYy48MZlRXL0u0V7Civk+QjICc5kl8f3YsHZ6znmR9zSYl2cuawNG45qa/VoUnyIYTVGnT/NOthIbTGi+n1okZGEj5mzAGPS7z+N0GKaN/8yZCX0pdfpvyNN4N+/cb5Pab2mRr0a+9P2dYC4oglJjHe6lAIZr1puMN/O/slt5QT+icH7bqh7t6pAzlhQBKrdlWyelclj327kRMGJDMk3dom3tD5tBMhTWY57Tj1gfkKXCHU6c/0ev3NGyFO0TRUl8vfr8HRsd/m98UwDX4z7Df0jrF+xsgmgar15BTrRjWYXn9CbQT6HATDtcf2AuD5OVtYsaMiaNcNZRsKq7nt3eW8Pm8bVfU+BqZGA1Dj9lkcmSQf4iAo0uujQzUEFpgLC6FmF9Pr9fe36CRMjwfV7gj6db2GN+idTdti6Dpuxdr+Q3pZAwDegtqgXfP4/sm8cLm/j8vZz/xMbQjcYK20rbSW8/87j6XbK6hxe/lo6U4e+3YjA3tEMzbb+lqx0Pq/RohuqMDtBcAVSs0uPl8nSz68KI7gJx8+w4ddDa3fk6mb6IphaQxarL+/iSM9uH0vJg9OZWh6DKt2VfLAjHU8eO7QoF4/lDz+7UaiXXa+/N0xRLnsmKZJcbWbuHAHWgjUsobOp50IaaYMtu0wZV7/N7RkC5oN9qfT1XxYFK/X8IZg8mGgK8Fr7tgXxea/tSjO4I4CAvj8Fv9Q2+kLtrM2vyro1w8VeaV1jMiKJcrl//tUFIWUaBcOW2jc9kMjChHSrM+Ru7bGNV4SHaFTEdlZ+nw0Mj0eS2o+vHqoJh/W1nw09hGzamjn29eOB+D0J+dacv1QcOKAZGasKuCDJTutDmWfOs+nixBdVOPqtqGwwNzamnoqfTq7o+Pp47P22/OhsCr58Jk+7FpoJR/4THTV2uSjOfuw5vLjezX3adhUVE3flChrArHQb0/IIb+inj9+sAKHTeWsEJlWvZEkH0JYzBPocOrowHbYBt2gRjdwqQqRtuaqcNM0WVJVh9swqDdMfrVyi3/HCWcyZftmXu2wiNqXFc0uuuFfZTaU5vgAQDctb3ZpHHFT/NwKUBSiT8ok+oTgrbvScuG0xMh9z3fS1amqwoPnDmV9YTW/e2dZyCUf0uwiDor0+Og4XtNEBbQOrPkY/8tahvy8mpy5q1hVXddUvrHOzdSlm5i2PLcp8Xh1SDZDSgrwaSF2Uz0AK2o+6n31AOyo3hHU67bFNEx01dr/Y+0p4cRd2I/Yqb3Roh34iusti+XNX7ZZdm2rqapCXLg/KZ+1odjiaFrrPJ8uwjIh0BrQpXkMc7+1Hm7dzS+75sPHMxk+7BR8GzZS8p8nUCMisKelkf3u/1DDD7xmQ+qPy1s9r2gx90LjVXuFOXhlSC9URaFfuJP/6DrOTpRyHmryYZomdZUVmEZz84QzMhK74+C/Jdf5/Elcfm3+wQcaDLqJYXGzi6IqRIxKAaBueYklzS/H9k1k7qbdDOwRHfyLh4iCynq27K4lIcLBiMxYq8NpRZIPISzmNcx99veo89Yxfvp4whpMXn9Op4BPmvZFTppE1YwZ6FVVrZKP6gYvK3dWoioKDpuCTVVRqjygKdw4II1nd5Tw0NYChkWFEWO3UReYXbV3mIuBkWFN5/GoGg6fu+PedDszvV7UiIiDPn7V9zP59sWnW5XFp2Vw6QOPoWoams2Oqh14pIZT8ycqJ2WddOgBdyTDxFBCJ3F8Jc5kVqwb59JNqApoKGiKgqbQ9Bhjs/Fwv4x2m+vGpxvM3bQbgJ4JobWg2pFo8OrM2lDC6l2VhDk0rpqYTcR+VqktrGzgkhd+waebfHLz0cSGB79P1IFI8iGExbymiX0fNR+PLn4UgNOHnk/FVTXEvuZfNjzzhefBNKmaMYMdN91E5rPP8ubmeh77ZgO1nr3b+hu/y9dHxmBXFJZW1dH/p9Vc2iOe6QVlgH8h05bcmkZnaik3fb5DqvmorSzHFRHJlFvuAGDzwvms+uEbnr76IgA0m41L/v4oKb1z9nsOw/QnbqoSWq3Xig6Gxc0uLX0fBVWqybgwR2DtORO98RGTUo/O17uruCEzqVUCfCRy7vmqabtfF+lsur20jkte/IVdFfWkRDupqPMyP7eUN349DnUfnx///nYDNW4fH990NJnxoZeASfIhhMU8holjHzewe4+6l2+3fcvmis3c/6e3WPfal2wdlUr/Y47BrK5GP+5E3HN+YOfK9XyZ6yA23ME9Z+QwMisWl13Dpxt4dZOCejfXvLiQ3bVu5hzbj09LKni/pJxV1fUMjnRxfHw012cktY5J1XB2oua2Qx0abBomNqeT3iPHApAxYDC9R41D93lx19ay6Z1Z1L+wnfzoUhSbiqIpKDaVsOFJRB+fCTQnH8uKloVW7YcBZgglH4ZiMt5n48mBPfe5f2FFDWct24zaTu27n69obgZ7+coDr03Umfzn+42Ypsk3tx1Hv5Qoft68m1+9vICXf9rKdcftPb3/mvwqTh6YEpKJB0jyIYTlvKbJvub9URSF4zOP55PNn5Bbkcv2nGh6LS3k60tP5PT/zeLdIpVLgRs+WMvmxGwuP6onl47fe0RBtlfHVODbudv5du72pvK8h8/Yb0yezljzYT+4j7NVP3zDim9noNmaR8c4wsLJGXtU0/Pqr7djw07kuFRMn4npM2hYX0bD+rKm5CPWGUuMM4a8qrx2fS9HStGxfqhtC2vCFNbg4+iF27ho3N4JiC8wz03dz7uo0uygKSiq4n/UFBRNxavXUBuxDEePeDQ1jJKSatzuFOx2JzabrenHh8Kd7ywCHFw/qTcnDUwJ8rvtOCt2VHDKoJSmmpyjcxL59dG9eOSbDYztFd+qT0dlnZdNxTVcMDrDomjbJsmHEBbz6AZp7lKoygdFBZsL7GGgOfAa/qnXoxxR9Pn7P6m4/ne4iioAOO1XZ+C77wf+Pv8l3hpwKr0qF1I2Npn4Hq1rMcLtGg9fPpJNZXV8tiKf3Tuq245Js3Wqmg/d68OnhWHoBmob/QbyVi5DtdmYeOFl+z0mJimV6rJyMk4+tqmstNqDUd28ZoqmaoxMGhlys/+quoKhhVZMAM/sLuMi9k4+PCX+kTANCwqpUTQwTEzd/4NhoCv1bD7pRqgDSppft3HDBIqK9m4Wu8gFP3hyuHvKwI56K+1iybYyXpyzlbzSWgalRTMqK46BPaIZlRW71+RsxVUN5JXW8ZvjWnee/eOp/Vm6vZxrX1/MxzdNJDM+HNM0efy7jWDCGcNCa3htS5J8CGGxkRunc9+if8CsPfcomEnxhEdGkRyeTPLIZL4c0wvXev/QwaMvOI1twwaw+4qruHHVJwDMU31Mfeofe13jkkFp3D1rQ1Piccmp++/LAOCx2XB0omFOi2LOpKwwC26ehaoq2BwqNoeG3alhc2o4Ao92h0bh5jLCo1MZcvzJ+z+habLXEA3TRK/xUreyBMWuothVelTEUxoZWlN4q4aCbg+d5KPwhBHcMmM1a9j3Qm++wGR2KdcMIS1t72Xety9+GwK/4mOO/gVdr2Pe/BMZNHgAV155Oz6fD5/Ph9fr5e3PvqFqVy6nZof2rW1e7m6ufGUhfZIiGZEZy/IdFXy6PB/dMDljaA+euWxUq+NfnZeHy6YyZWiPVuUuu8aLV4xh2nPzOPPpnxiWEUt+RT2bi2u4d+ogkqJCt/4ytP+FRMgwQ+ezrMtxNlT4N1KHwQl/Bl8DeBvAV0+vhY8w09Sb1xAxoeVNsWf/bJK+n8Gi/31O8qP3k3LU2H1eo9LtZfrXm1GAey8dzjXDDlwd69FsuEJg8amD1aBF0iOikoHTxuPzGP4fr463Qcfr0fG6dXxu/2NdtRtdP/BIFv+fe+v3b4tzUb9yN2XT1zeVXcHJrEvZDqe2/3s6XKqh4NVCp9kFwDBNbPv5c9IDzS7afmqszMC0NHZPEk5nEobhRVHAZnMR3mKkV1VtA1W7cgE4YfyIdou9I7w4ZwsDe0Tz4Y0TsQfet1c3+N/C7dz76RquyitrWnlWN0ze+mUblx3Vk2jX3hPpJUY6+fDGiTzx3SaKqhoY1yue+6YO4rh+SXsdG0ok+RBt6jy3oM7J5qsjPzyDtBv2XodiyZr/kmN4WqwfYmLu8Q8SHhlO1aw5EJXIsRdP3ec1nlq8DQXoMzixzcRDN018NhvOEFplty0GKrFhHgZObLua+bnrFbQDdE4tXLgOtcpkz6n1Yqb0InpyT0yv4f/x6Pzy8pc49ND6GNV0FVMLranxfabJ/v6cdD2QfOwn2e0x4nQ2L74Pl8ffn8kw/EPAFaV5dJNhGPz7kYebno8e3Lc9wu4wDpuKqihNiQeAXVO5bHxPXp2Xx3uLdjQlH3mltVQ3+JjYJ2G/50uMdPL3c4Z0eNztqfN8ugjRRdm8dbht++6RnulKwG20qK42zX3O+qaUlhDRUMO3f/sPNRV7NwMogRTyimHpbcbjDnwTdXaimg8DDW1/X633PFbXDziHR9lHG4kxEvC59r6BK5qK6rKhRTmwJYThUb17JYNWUw0l5D7ZddPEtp+vMbq5/5qPhopi5i72j1jJ6Pcr//F6Y/LRXAvwzPvfNG1fcu3NOG3BX033UJwzIp3lOypYvauyVbmqKvSIcVFe19y36P3FO4ly2RjXYr2ariDE/kRFqJJWl45j99bhtu17foM+MX3YqYHp838Ymftp/8q+8w4Keg+hx3uvsvGY45j19Out9o9NjwGbwmPfb2ozHndg1s9OVfOh2NAOcqlwQ9cPWPMRTTw14dUM/eu5bZ5LQQm5DqeaoWKG2L1XN/e/fICn1N/hVDNMfA01LJxxId//0Ifvf+jDz0snNB2X2s9fq+fTG/yvczc3LW3f6m9umXTWxfTPCO3mBoCTB6XQJymCP36wkvoWc/Ns3V3LL1vKmBRoMmnw6ry7aDsXjskkPIRWvW4Pirm/TzOLVFVVERMTQ2VlJdHR3Xda3FDymzV5fFZcQZar7Umctjf4b5KZLgcmZpt9RVp+Hiktvhnt+THV8nnr1+x53L7PcaDX7Pf1yp772t7e+1ptv6dvvhzn3+gxIvBipenxFV8xj4fD8KThKCgcM30Nxyytx5GQBDYbiqahaJp/W1VxFxVDlf/b1J03vYCqqSiAqsDS7RUQZWfElF4H+A34h/4uqarjwWf+xUmuINzFVNX/Y5pNP6Zp+DNe0z/iAdP03+SNfR/zVeotACSkN85yqrR6gOZ/l50r/wZAUs9egfMSOJ//j/Vk+yUA2JICCWHLv+Gm4/1PGypqWBCxiuf7foyqqKiKiqZoKCgoitLq0R9DoCxQvq+y/R2roPj/NPZ8/R7HXz9/KqneBBxhrn38oTb/Xlo+bS5ocewe/9Mo7F3W+nes7OP37S/7Q4rBtyk2hraYRKzx0PLKBnZoJj8sqKNg3OXsS0z0yKZr67qbmpo1rFx5MjHR4wHYvt0/hHxtymRMBdYXVlPd4OO7248jJzk0JxlbV1DFec/O46SByTx1yUgAzn12HmW1Hr669VginDbeW7yDuz5cyY93HE924sHP4GuVQ7l/d61USnSIGzKT6BV2cL2mvyypoMzr47yUOAK30f0y97MNrb/h77XvgK9rua/13gO9DnP/+1qe58DXO5Q4m0sW9TqHUTtmoqWN9B9pmk2PE3wZrLU14IrOxsSk4uw4ygdp9I/JAV3H9Olg+B9NXSdc91FfXcfiegdDM2MxTRPD8Hf4i4h2UhNrJ/0gksjsvC0cNaAPdq+nzWOPhGkGEgpDpynpUtXApuIfeqw0ljfecJuPQVFQFJWYklrC05JI7B3X4uRNF2n1tHb3MDx1u0jrP6jpBum/lv9GXlJWREpsL1zJgXM1/SHvfeOuqTPRYuK4KPEiDNNAN/0r3Rqm4f+7MQkk4f7kqXHbH0+L8sbkqsXv5WCP3/PYJcO2crIzg/iIHoHkrNUvfO/N/f0RN2ZZZuunLcv2/B3veY7G2C9TfaREO9Ai7XtfJtxF7I5akvvZKQiUpSaei2q3B95jYwAmjf83lpZG0SP1KJzOWADqDI2FFRFkBKZSX5RXDsDaguqQTT4G9ojm3xcO58a3l5KTHMnY7HiW76jg7WvHE+G0UVBZzz+/Ws/kQSmdIvE4VFLzIYQQokt56Kt1PD/bv0rz1odO32vejFDy0FfreGHOFi4/qicfLtnJyvtPZVd5PVe8sgCPz+DzW44hITJ0h8y2dCj3787TqCuEEEIchPNGNo/oWrmz8gBHWs9l07CrKicOSKbOqzP+we84+d+z0U2Td6+f0GkSj0MlzS5CCCG6lP6pUcy98wSO/dePzFhdwPAQW06+0derC3jmx81cfXQ2x/dP5sMbJ/LDumJiw+1cMi5rvyvWdgVd950JIYTotjaX1ACQW1xjcST75tMNbnt3BZP6JXHXaQMAGJUVx6isuDZe2TVIs4sQQogup87tH8L63bpiPmux0m2oUBWFCKcNTVX2O8FaVybJhxBCiC7nlEHNK9r+7p1l9PnzDH47fSmVdV4Lo2qmqgr/OGcI36wt4vk5W6wOJ+hktIsQQoguq7iqgce/24jTpvHavDwAFt5zEslRLmsDC3hoxjpe/TmPr35/LH2SIq0O54jIaBchhBACSI528dB5w7j/rMHcN3UQADNXF1ocVbPbTulHUpST/3zX9uzDXYkkH0IIIbqFvin+moWU6NCo9QBw2TXCHRrOg1weoKuQ0S5CCCG6hXs+Xk2U08ZJA1PaPrid1bh9fL4in1q3j4RIB9kJESRFOZmfW8qm4pqmES/dhSQfQgghujzdMNleVscZw3oEfXSJaZpc+/oiFmwtI9yuUetpvWLymcPTOGlgclBjspokH0IIIbq8T5fvAsBuwbDWOo/OL1vK+NOUAdwwqQ+V9V7m55by0dKd/O6kvgxOiw7pKeA7QvdqZBJCCNEtnT60ByOzYpmxupDiqoagXjvCaePYvom8OGcLX68uINpl47QhqbxwxRiGpMd0u8QDJPkQQgjRDbjsGkmRTny6QbXbF/Tr//vCEYzIjOWGt5by2+nL2FFWF/QYQok0uwghhOjSvLrBvNxSvllbxFUTsy2ZTyMpyslLV47h85UF/N/Hq/hqdQFZ8eFcOTGbq4/uFfR4rCbJhxBCiC7rwyU7ueP9FQAkRDi46fg+lsWiKApnDU/j5IHJfLo8n5fmbuGfX6/nygnZqN1sinVJPoQQQnRJbp/elHi8+5ujGJ4Zi8uudeg1V+yo4LZ3l9M7KQKPbuL1GQxKi+b0oamMzPQvGvfNmiI+Xb4LRVFo8BrUe/UuvYLtvnSvdyuEEKLbuPeT1QD8+8LhjO+dEJRr/uPLtWzZXUt6XBgRDhuay8ZnK/J5+aetRLts6IZJrUdnQu8Ewh0avz+5b7dLPECSDyGEEF1MZZ2XM56ay87yegCO7x+8OTRGZsWxKK+cUVlx3HJiDjZNRTdMFueVsSivDJumMr5XPCOz4oIWUyiS5EMIIUSXsLO8jpveXsrKnZUAxIbb+eSmo4mPcAQthj+dNoAIh40nvt/IrA3FPHrBcPqmRDG+d0LQal86A1nVVgghRKe3cGsZV76ykP9v796joir7PYB/Z3xlAGVAkNGQEfOWYAKGmYjlK8VFpYXV6eLJLgfLfNXTqsyA43pFKbUVpZEuzZXHC6eVWpTFytsCtdQwRS6J+Aq8ikECgYCACsNlnvMHAk5azODsvRn8ftaapTP7mZnf/q49zG/t2fvZDc2teHaCHs9N1MNf76LYHBpZxTVY8tUvKKluwOLQ0Xjl4eGyz6wqN0u+v9l8EBGRTYtOPo1dp0oAACmLguDr6aJsQTc0NrdiTWoBPjt6AeOGOGPVE+Nw/xBnpcuSjCXf35xkjIiIbFbmr9XYdaoEQSPdcHDx1B7TeABtE5v9zwxvJM8PRHOrwDObjiOruEbpsnoENh9ERGSzTl1s+zL/v6iHFJk8zBwBXq745h+T4X2PFq/vyIahpbXrJ/VybD6IiMgmXTW0YFdGCYa4OPT4Sboc7PogOnwMfqtpQOHvV5UuR3FsPoiIyKa0tBqRfv4ywtYeQVHVNfx38EilSzJL6ZW2U3/vxnk9/ogJEBGRzdj4w3msTStAU4sR9w/R4uPn/PHgMFely/pTRqPAz0VV2PrTRaT963f8/T53DHNzVLosxbH5ICIim/DzhSokHizAMDdHvP+UL/w8XXrs6au1Dc1Ym1qA70+X4fJVA0bp+mPVE+PwHwGeip3+25Ow+SAioh4v/d+X8Z+bT2CIiwM2v/gghvbgvQctrUa88L8nUFR5Dc9N1CN07GBM8BrApuMmbD6IiKhHa2414tMjFwAA3y4MgruTRuGK/tq58nqc/q0WSVET8chod6XL6ZF4wCkREfVoScd/xZGCSsRMH9PjGw8AuFh1DQDg69l7JxS7UxY1Hxs3boSvry+0Wi20Wi0CAwOxb98+kzHHjx9HcHAw+vXrB61Wi0ceeQQNDQ1WLZqIiO4OVw0t2HKsCADwX0HDlC3GTL9WXYezQ1+4OMp3TRlbY1Hz4enpiffffx+ZmZk4deoUgoODERkZiby8PABtjUd4eDhCQ0Nx8uRJZGRkYNGiRVCruYOFiIgst/7Qv3HpSgO+/sdkaP7WR+lyzPKvsjqM1PXMCc96iju+tourqysSEhIwd+5cTJo0CSEhIXj33Xe7/Xq8tgsREQHA5asGTHgvDWMGO2H/G48oXY5Zfqu5jrC1RxA15V4sDr1P6XJkZcn3d7cPOG1tbcVXX32Fa9euITAwEBUVFThx4gSef/55TJ48GefPn8eYMWOwcuVKTJky5U9fx2AwwGAwmBRPRER3N6Ox7VooADB3yr1IP38ZQgBGIWAUbcs7/i/Ejfvty2/cjG3325/XemO8+MN4IXBj2Y2xJstuft0bzxWmzzXe9Ng3Wb9hYH8NXpkyXOEEezaLm4/c3FwEBgaisbER/fv3x+7du+Hj44Off/4ZALB8+XJ8+OGH8Pf3R1JSEh599FGcOXMGo0aNuu3rrV69GitWrLiztSAiol6loKIeFyrbDtxcknzaKq+pUgF9VCqoVSqoVIBapYL6xr8qFdBH/cdlbctVKhXU6s7Hbvs6N5Z736NFTPgYODv2tUrNvZXFP7s0NTWhuLgYtbW1SE5OxubNm/Hjjz/iypUrCAoKQmxsLFatWtUx3tfXFzNnzsTq1atv+3q32/Oh1+v5swsR0V2uuOo6mlqNHQ1CH/UfGgO1aZOgVqtMGoqbGwXVjSaCpCPpzy52dnYYObJtHv2AgABkZGQgMTERMTExAAAfHx+T8d7e3iguLv7T19NoNNBoev6pU0REJK+ePJEY3Zk7Pg3FaDTCYDBg2LBh8PDwQH5+vsnygoICeHl53enbEBERUS9h0Z6P2NhYTJ8+HUOHDkV9fT2++OIL/PDDDzhw4ABUKhWWLFmCuLg4+Pn5wd/fH9u3b8e5c+eQnJwsVf1ERERkYyxqPioqKvDiiy+irKwMzs7O8PX1xYEDBxASEgIAeOONN9DY2Ig333wT1dXV8PPzQ2pqKkaMGCFJ8URERGR77nieD2vjPB9ERES2x5Lvb049SkRERLJi80FERESyYvNBREREsmLzQURERLJi80FERESyYvNBREREsmLzQURERLJi80FERESyYvNBREREsrL4qrZSa59wta6uTuFKiIiIyFzt39vmTJze45qP+vp6AIBer1e4EiIiIrJUfX09nJ2d/3JMj7u2i9FoRGlpKZycnKBSqW5ZXldXB71ej5KSkrv+2i/MwhTz6MQsTDGPTszCFPPodKdZCCFQX18PDw8PqNV/fVRHj9vzoVar4enp2eU4rVZ7128o7ZiFKebRiVmYYh6dmIUp5tHpTrLoao9HOx5wSkRERLJi80FERESysrnmQ6PRIC4uDhqNRulSFMcsTDGPTszCFPPoxCxMMY9OcmbR4w44JSIiot7N5vZ8EBERkW1j80FERESyYvNBREREsmLzQURERLKymeYjKysLISEhcHFxgZubG+bNm4erV6/eMm7btm3w9fWFvb09dDodFi5cqEC10jMnD5VKdctt586dClUsLXO3DwCoqqqCp6cnVCoVrly5Im+hMugqi6qqKoSHh8PDwwMajQZ6vR6LFi3qtddT6iqPX375BbNnz4Zer4eDgwO8vb2RmJioYMXSMedz8vrrryMgIAAajQb+/v7KFCoTc/IoLi7GzJkz4ejoCJ1OhyVLlqClpUWhiqVTUFCAyMhIDBw4EFqtFlOmTMHhw4dNxhw8eBCTJ0+Gk5MTBg8ejOjo6G5nYRPNR2lpKR577DGMHDkSJ06cwP79+5GXl4eXX37ZZNyaNWuwdOlSxMTEIC8vD2lpaQgLC1OmaAmZmwcAbN26FWVlZR23WbNmyV6v1CzJAwDmzp0LX19feYuUiTlZqNVqREZGIiUlBQUFBdi2bRvS0tIwf/585QqXiDl5ZGZmQqfT4fPPP0deXh6WLl2K2NhYrF+/XrnCJWDJ5yQqKgrPPvus/EXKyJw8WltbMXPmTDQ1NSE9PR3bt2/Htm3bsGzZMuUKl0hERARaWlpw6NAhZGZmws/PDxERESgvLwfQ1qTPmDED4eHhyM7Oxq5du5CSkoKYmJjuvaGwAZs2bRI6nU60trZ2PHb69GkBQBQWFgohhKiurhYODg4iLS1NqTJlY04eQggBQOzevVuBCuVlbh5CCLFhwwYxdepUcfDgQQFA1NTUyFyttCzJ4maJiYnC09NTjhJl1d08FixYIKZNmyZHibKxNIu4uDjh5+cnY4XyMiePvXv3CrVaLcrLyzvGbNy4UWi1WmEwGGSvWSqVlZUCgDhy5EjHY3V1dQKASE1NFUIIERsbKyZMmGDyvJSUFGFvby/q6uosfk+b2PNhMBhgZ2dncqEaBwcHAMCxY8cAAKmpqTAajbh06RK8vb3h6emJZ555BiUlJYrULCVz8mi3cOFCDBw4EBMnTsSWLVvMutSxrTE3j7NnzyI+Ph5JSUldXvTIVlmybbQrLS3FN998g6lTp8pSo5y6kwcA1NbWwtXVVfL65NTdLHorc/I4fvw4xo0bh0GDBnWMCQsLQ11dHfLy8uQtWEJubm647777kJSUhGvXrqGlpQWbNm2CTqdDQEAAgLa87O3tTZ7n4OCAxsZGZGZmWvyeNvEXODg4GOXl5UhISEBTUxNqamo6dvWUlZUBAC5cuACj0YhVq1bh448/RnJyMqqrqxESEoKmpiYly7c6c/IAgPj4eHz55ZdITU3FU089hQULFmDdunVKlS0Zc/IwGAyYPXs2EhISMHToUCXLlZS52wYAzJ49G46OjhgyZAi0Wi02b96sRMmSsiSPdunp6di1axfmzZsnZ6mS604WvZk5eZSXl5s0HgA67rf/HNEbqFQqpKWlITs7G05OTrC3t8eaNWuwf/9+DBgwAEBb05Weno4dO3agtbUVly5dQnx8PIDubT+KNh8xMTG3PSjy5tu5c+cwduxYbN++HR999BEcHR0xePBg3HvvvRg0aFBH12o0GtHc3IxPPvkEYWFhmDRpEnbs2IHCwsJbDprpqayZBwD885//RFBQEMaPH4/o6Gi88847SEhIUHANLWPNPGJjY+Ht7Y05c+YovFbdY+1tAwDWrl2LrKwsfPfddzh//jzeeusthdbOclLkAQBnzpxBZGQk4uLiEBoaqsCaWU6qLGwV8+hkbhZCCCxcuBA6nQ5Hjx7FyZMnMWvWLDz++OMdjUVoaCgSEhIwf/58aDQajB49GjNmzACAbuWl6PTqlZWVqKqq+ssxw4cPh52dXcf933//Hf369YNKpYJWq8XOnTvx9NNPY+vWrYiKikJJSQk8PT07xg8aNAjvvfceXn31VcnWw1qsmcft7NmzBxEREWhsbLSJ6xhYMw9/f3/k5uZCpVIBAIQQMBqN6NOnD5YuXYoVK1ZIui53Supt49ixY3j44YdRWlqKe+65x6q1S0GKPM6ePYtp06bhlVdewcqVKyWr3dqk2jaWL1+Ob7/9Fjk5OVKULRlr5rFs2TKkpKSYZFBUVIThw4cjKysL48ePl2o1rMLcLI4ePYrQ0FDU1NRAq9V2LBs1ahTmzp1rclCpEAJlZWUYMGAALl68CB8fH5w8eRIPPvigRbX9zbJVsS53d3e4u7tb9Jz2XV5btmyBvb09QkJCAABBQUEAgPz8/I7mo7q6GpcvX4aXl5cVq5aONfO4nZycHAwYMMAmGg/Aunl8/fXXaGho6BiXkZGBqKgoHD16FCNGjLBe0RKRetswGo0A2n6esgXWziMvLw/BwcF46aWXbKrxAKTfNmyNNfMIDAzEypUrUVFRAZ1OB6Dt+EKtVgsfHx/rFi4Bc7O4fv06gFv3YKjV6o6/De1UKhU8PDwAADt27IBer8cDDzxgeXHdPTpWbuvWrROZmZkiPz9frF+/Xjg4OIjExESTMZGRkWLs2LHip59+Erm5uSIiIkL4+PiIpqYmhaqWTld5pKSkiM8++0zk5uaKwsJCsWHDBuHo6CiWLVumYNXSMWf7uNnhw4d75dkuQnSdxZ49e8SWLVtEbm6uKCoqEt9//73w9vYWQUFBClYtna7yyM3NFe7u7mLOnDmirKys41ZRUaFg1dIw53NSWFgosrOzxWuvvSZGjx4tsrOzRXZ2dq86u6NdV3m0tLSI+++/X4SGhoqcnByxf/9+4e7uLmJjYxWs2voqKyuFm5ubePLJJ0VOTo7Iz88Xb7/9tujbt6/IycnpGPfBBx+I06dPizNnzoj4+HjRt2/fbp9RaTPNxwsvvCBcXV2FnZ2d8PX1FUlJSbeMqa2tFVFRUcLFxUW4urqKJ554QhQXFytQrfS6ymPfvn3C399f9O/fX/Tr10/4+fmJTz/91OS0st7EnO3jZr25+egqi0OHDonAwEDh7Ows7O3txahRo0R0dHSvzEKIrvOIi4sTAG65eXl5KVOwhMz5nEydOvW2eRQVFclfsMTMyePixYti+vTpwsHBQQwcOFAsXrxYNDc3K1CttDIyMkRoaKhwdXUVTk5OYtKkSWLv3r0mY6ZNm9bxd+Ohhx66ZbklFD3mg4iIiO4+veOQXiIiIrIZbD6IiIhIVmw+iIiISFZsPoiIiEhWbD6IiIhIVmw+iIiISFZsPoiIiEhWbD6IiIhIVmw+iIiISFZsPoiIiEhWbD6IiIhIVmw+iIiISFb/D5eh1UZ9eID8AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "print(\"here is the final border set\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "173bb175-312b-4d08-a5b5-80a1d5d70416",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "print(isContiguous(borderUnits,unitNbrs)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fc1ae6e1-ef52-412b-a966-e9739071af8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#date_ = \"25May24\"\n",
    "#print(\"For safekeeping, write the unit topology to a file\")  \n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        #for i,uu in enumerate(surrounders):  #no longer tracked\n",
    "         #   if u == uu:\n",
    "         #       unitVTDlist[u].append(surroundedVTDs[i])\n",
    "                \n",
    "unitNo = [u for u in range(nUnits)]\n",
    "unitCPx, unitCPy = [unitCP[u].x for u in range(nUnits)], [unitCP[u].y for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"neighborList\":unitNbrs, \"unitVTDlist\":unitVTDlist, \"unitParentVTDno\": unitParentVTDno, \"allUnits\":allUnits} )\n",
    "#outname = STATE+\"unitTopologies_\"+date_+\".csv\" \n",
    "#outpath = \"state_map_files/\"+outname\n",
    "#nbrDF.to_csv(outpath)   #commented out, we are not writing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "d4baaea4-7af4-4407-aeb3-f4291d335f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "vtdGeom = tractGeom.copy()  #optional reset if we need to rerun the below clipPoly routine with alternate clipPolys\n",
    "nHDs = len(tractGeom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "abdd07e7-f9be-480a-9d3d-b3948eeaaa2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "toSquishCountiesList = list()   #default; if we did not have any clipPoly's to move in\n",
    "nClips = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3882b978-b0f8-45c3-b9c3-5d43eab89669",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In the next few blocks, we define a VRA core that stays together.  The core is included\n",
      "in all HDs inside a defined envelope, and excluded outside this envelope\n",
      "To determine current minority fractions of these unit-based lists, we must establish unit --> VTD conversn\n",
      "working on full or partial VTD master list for unit 0\n",
      "working on full or partial VTD master list for unit 2000\n",
      "working on full or partial VTD master list for unit 4000\n",
      "Now, let's compute minority and total VAP of each unit\n"
     ]
    }
   ],
   "source": [
    "print(\"In the next few blocks, we define a VRA core that stays together.  The core is included\")\n",
    "print(\"in all HDs inside a defined envelope, and excluded outside this envelope\")\n",
    "#THIS WORKS FOR BOTH VTD- AND UNIT-BASED (FRAG VTD) -- **NOTE: DOES NOT ADD IN CUT DISTRICTS AND REBALANCE WEIGHTS\n",
    "print(\"To determine current minority fractions of these unit-based lists, we must establish unit --> VTD conversn\")\n",
    "noFrag = 0 #int(input(\"enter 1 if there were NO fragmented VTDs\"))  #for simple states where units are at least whole vtd's\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist, unitFragVTDlist, unitVTDfrac = [list() for u in range(nUnits)], [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "unitFullVTDlist, unitPartialVTDlist =       [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "\n",
    "for u in range(nUnits):\n",
    "    if u %2000 == 0:\n",
    "        print(\"working on full or partial VTD master list for unit\",u)\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "        unitFullVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "            unitFullVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        if noFrag == 1:\n",
    "            unitVTDlist[u].append(allUnits[u] )\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitVTDlist[u].append(surroundedVTDs[i])\n",
    "        else:\n",
    "            unitFragVTDlist[u].append(allUnits[u])\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitFragVTDlist[u].append(surroundedVTDs[i])\n",
    "            vtdFrac = [0. for V in range(nVTDs)]\n",
    "            for vv in unitFragVTDlist[u]:\n",
    "                V = parentVTDno[vv]\n",
    "                if len(VTDchildren[V]) == 1:  #nonfragmented vtd\n",
    "                    vtdFrac[V] = 1.\n",
    "                else:\n",
    "                    if tractPop[V] > 0:\n",
    "                        vtdFrac[V] += fragVTDgeom[vv].area / vtdGeom[V].area #fragVTDpop[uu] / tractPop[v]  #we overwrote the frag pops earlier; can't use\n",
    "            for v in range(nVTDs):\n",
    "                if vtdFrac[v] > 0.0001:\n",
    "                    if vtdFrac[v] > 0.999:\n",
    "                        unitFullVTDlist[u].append(v)\n",
    "                    else:\n",
    "                        unitPartialVTDlist[u].append(v)\n",
    "                        unitVTDfrac[u].append(vtdFrac[v] )\n",
    "\n",
    "print(\"Now, let's compute minority and total VAP of each unit\")                        \n",
    "unitVAP, unitWhiteVAP = [0.]*nUnits, [0.]*nUnits\n",
    "for u in range(nUnits):\n",
    "    for v in unitFullVTDlist[u]:\n",
    "        unitVAP[u]      += tractVAP[v]\n",
    "        unitWhiteVAP[u] += tractWhiteVAP[v]\n",
    "    for i, v in enumerate(unitPartialVTDlist[u]):\n",
    "        unitVAP[u]      += unitVTDfrac[u][i]* tractVAP[v]\n",
    "        unitWhiteVAP[u] += unitVTDfrac[u][i]* tractWhiteVAP[v]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f81ded30-89a9-4b38-8574-22ab3d685460",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and now the vtds in mear-StLouis counties with vtd mVAP > 0.45\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now draw a box approximately around the near-St L high-minority area\n",
      "the core pop is 0.79285 of a district\n",
      "its mVAP fraction is 0.60687\n"
     ]
    },
    {
     "data": {
      "image/png": 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TTVhiMmb/AKoKCwhPbtN8TkNVJZUFeWh1OiJTDxyuOpW1PLR6PcnderF7zYqjzrMRDq2uvBSjl/nc2afJZSXQz5NYZ1c00S1OJCzHRG9Ge/6zJPa7A+eCV8mZ9RHynClE9xuLru+tYqjoDCUSFuG0cjrs5G/bgiRJxHXo0uqfcvVGEymHKMfujomlYMd2zP4BRKSksnf9GiRZRlVVfIKCie/UFZfdTt62TWg0OuI6dj4t8eqMRuI7dSVz5VJSevU7e1e3tAKn3UZZzt6j9pSdNdwuUFzoDCai/E1kn8lLm89UPuHoLnqDpCH/wb36YwqW/oR78XR8opII6TMeqf0l4HOiU4OFliZ+2wmnVe6mDcR16oLeaGrtUI4oe9N64jt2QVVVynOz0eh0+IaEEhQV03yMzmgksUsPLPV1ZK1fQ/JpGtIyeJlJ7tmXnM0b8A0OITQ+8bRc92ymKG6y1q0mre85VB7eZfP8rTWSGGIm52xY2nym8otCc96zxA95BDJnU792Gtk/vw4/v050zxEYhj4oel3OAGIgXDitknr0InfLRirzc1s7lCNSXC4Kd2awZ80KvPz8SOjcDVmW2bN2JXXlpQcc6+XrR1hCEkWZO09bfFqdjuTuvZA1GrI3rUNV1dN27bPRnjWrSO7Z59ya++PaV41ZayQh2EyO6GE5eXov6HApvjdOI+mZtSRedA/l21aS9dJIXHOfAqettSP8VzuHfnqFs4Esa2jTqx+SLJO7ZWNrh3NYqX0GkNC5G216928uTBcQEUVKz77UFBdhqattPlZVVRS3C4fl9N8wgmPiiEhOZdfKpbicopT/oeRsWk9Meodzr46Ny+r5W2ckMdhMTlUTbkUkri3GKxCp3z3ETF5DwqibyJ33LeWvD4HyXa0d2b/WcSUsH374IR07dsTX1xdfX1/69OnDnDlzmp8vLS3lmmuuITw8HLPZTNeuXfnpp5+O2GZDQwP33XcfcXFxmEwm+vbty7p1607s1QhnjaDoWIJiYineffp6JVpKXKeulOd49kKpLS0ha+0qXA4H8SewrLolmHx8Se3dn6y1K7FbLK0Sw5mqePcu/MIiDlhqfs74ew9LiDcOl0JxrbV1YzoX6Yxohj1K8sO/IWs05L5xEeyc1dpR/SsdV8ISHR3Nyy+/zIYNG1i/fj1Dhw5l3LhxZGRkADBp0iQyMzOZOXMm27Zt45JLLmHChAls2rTpsG3edNNNzJs3j6+++opt27YxcuRIhg8fTlFR0cm9MuGMpzd6oShKa4dx3CRJQlEVaktLqCktJqVXX4KiY1t11Y6s0ZDadyA5m9e3Wgxnmupiz++QE11KfsZz7ktOtCYSgz11X8XE21MoNI3ge/4gtG03dn16L+75L8BZ+PvrbHZcCcvYsWMZPXo0KSkptGnThhdeeAFvb29Wr14NwMqVK7n77rvp2bMniYmJPPHEE/j7+7Nhw4ZDtme1Wvnpp5949dVXGThwIMnJyTz99NMkJyfz4YcfnvyrE84oZTl7ydm8gdzNG7DU15G7ZSMRf1sufDYxmn1w2KwnVKzuVJEkiciUNMqys1o7lFaluN1kb1qHtb6OyDZprR3OqdPcw2Ig0t+EXiuTU3EWleg/Gxm88Zr0NSljbyFr9udYvr5GzGs5jU54lZDb7Wb69Ok0NTXRp49nWWjfvn354YcfGDNmDP7+/kybNg2bzcbgwYMP2YbL5cLtdmP8xx4sJpOJ5cuXH/H6drsdu93e/HV9ff2JvhThNCjclYF3QBBhCUkoipuy7Cxi0juctaXmz9QboW9IKGU5WYQmJP3r6rRUFRVQW1qCLMvEpHc89+as/JNz3/CfzoRGlogP8hITb08HSUIz5L+kRnQg+7P7CfrkEvxu+FZUyz0NjnvS7bZt2/D29sZgMHDbbbfxyy+/0K5dOwCmTZuG0+kkKCgIg8HArbfeyi+//EJycvIh2/Lx8aFPnz4899xzFBcX43a7+frrr1m1ahUlJSVHjOOll17Cz8+v+U9MTMwRjxdal8NiwT8sHPBMvI1ITj035xWcAaLS0inamdHaYZw2qqqye80KUFWSuvUkoUv3cz9Zgf3LmnWeEgEJwWYxJHQ6pY0m8e6vqC/Jo/LdMVBf3NoRnfOOO2FJTU1l8+bNrFmzhttvv51rr72WHTt2ADB58mRqa2uZP38+69ev54EHHmDChAls27btsO199dVXnv1WoqIwGAy88847TJw4Efkoyw8fffRR6urqmv8UFBQc70sRTqOQuIR//VDF6eLl64etqRFFcbd2KKecqijsXr2c2PROBEXHtnY4p9ffelgAEkO8yRa1WE6vmJ7E3PsLTruV0rcvgMo9rR3ROe24Exa9Xk9ycjLdunXjpZdeolOnTrz99tvs3buX9957j88++4xhw4bRqVMnnnrqKbp37877779/2PaSkpJYsmQJjY2NFBQUsHbtWpxOJ4mJRy6GZTAYmlcr/fXndFMVhb0b1uC0iTHMo/EJCj5gKbBwasV16Ez+ti2tHcYp5XI62bVyKYldemD09m7tcE6/v+ZOaPf3sBTXWbE5z/1E9YwS0oaIe35DazBS+NZFUCBWuZ4qJ12HRVEU7HY7ln3LKf/ZM6LRaI5pJYjZbCYiIoKamhrmzp3LuHHjTja0U6IiP5fMVcvYtXIpWetXExKXSNa6VVQW5LV2aGe0yoI8/CMiWzuMfw2d0YiqKLgcjtYO5ZSwNTWStXYlqX0GoPvHHLh/DacFkEDrGf5KCjGjqpBbJXpZTju/KILvmoVPeAzZ714FO39r7YjOScc16fbRRx9l1KhRxMbG0tDQwLfffsvixYuZO3cuaWlpJCcnc+utt/Laa68RFBTEjBkzmDdvHrNm7V+zPmzYMC6++GLuuusuAObOnYuqqqSmppKVlcVDDz1EWloa119/fcu+0hbSVF1Fap8BBzzmO2AIuVs34bTbiEhObZHruJxOtLqzc0LqodSUFh9yzx7h1Int0JmsdatJ7dN6m0ueCvWVFZTnZpPad+C/bmLxAZxWz3DQvvcgIdjTy5RT0URa+Onvcf47W+lqKrI+p6okC0uVD6pbRgVkjRuvIBsBYZH4hw3FN2kCkvYcmW/kFYjfrTPQ/XALmZ/eT8plRch9bmvtqM4px5WwlJeXM2nSJEpKSvDz86Njx47MnTuXESNGADB79mweeeQRxo4dS2NjI8nJyUydOpXRo0c3t7F3714qKyubv66rq+PRRx+lsLCQwMBAxo8fzwsvvIDuLLtZx3fsQt62zVjqak94J9jq4kKqCvLRGgxotFpcTs+nY1VRiGnXAb3JqwUjPn1qy0rxD4to7TD+dTRaLdFt09mzbtU5kyxWFRbQVFt92vZtOqO5rM3zVwACvHT4mXStOvG2oXAee1a9Rm1xEMgqBr0v3sFNyFqQNDIum0JTlYGaUguqNBvpj1kEhFcQGdebwNQb0AYceoHGWUNnxOvKL0gMeJzMaa+RXJ2HbtQLcC5tCdGKjithmTJlyhGfT0lJOWpl29zc3AO+njBhAhMmTDieMM5Ycfs+0UamtsVps1JfUU50uw7NnwKddhuSJLN3w1o0Oh3hSSnUlpXgsFpABZOvLym9+h7Urqoo7N24rvmXtNvlQpblg/ZFcdps5G7bhFb3tx2QVdXzCeyvvwGj2ZuIlJbpCToW1cUFJHbpcdquJ+xn9g8gKrUdu9esIKVn37O6R6IiPxeH1Ups+06tHcqZwWkF3f4PMZIkkRhibpWJt257HXv+vJrivf5o9DradPElvMfzaE3Bhzxecdmoz/mJityfKc/2Y3tFDtK6yRgM5cS370B4t2eRDa3bS3TCZBndmJdIDYxjz/TXiCreiffguyA0DbzDQSP2HD5R4p1rYck9epO9cR2SJBGWlMKOpQuJ79SVoswd6A1GnA47fqFhhCUkUZ6bTUhsAgavI/ecSLJMTUkROZvWoygKTbU1GL290RkOHLt3O50kd+t11A3emmpryN607rQlEZIkPl20Ji9fP2LTO5G1dhV+YeFn5e7O5bnZuJ1OolLbtnYoZw6nFbQH/g7wbIJ4eovH2Sq3sGHWgzjqQonvCPH9vj1qsiFrjfinXIV/ylWkAJbqrVTu+YzSrDp2ra8ka/uVtB0wipC2d56eF3EKyH1uIzUwnpKfn6X845uQACQZn6hkggdfB+kXH9BDJhydSFhOgcSu+xOB+E5dqcjPJaXHwTvFhiUee/dn9zEXtdhOs2b/ACRJxlJfh5evH0WZO9EbjYTEJRxwnNNmQ6vXN1/X2tiAwcsLWdYc1/VUVUFxu5E1x3ee0HKM3t6k9OpLXXkpWevXYDCZiGqbftzfy9ZQmZ+L2+k8rb2CZwWn9aAbXlKINwt3lZ+2EOyVW1nz839B1dNjzHi8ky85oXa8AjsS2+stYntBY8E8MhY+z/Y/NhCWM460Ed8h687O4XBSzyfikfOgIhPqCqA2j7qNs9j71eNojS8SM/wa5N63gCmgtSM9K4iE5RQz+wdg9j/5/4wtlaz8xewfgN3SRP62zYQmJFFbWkJAZDRb/vydoKgYXC4XTqsFVVVpO2AITpuV7A1rkWSZlB59jmtlRnRaOnnbNp9RZez/rfxCw/ELDcdusZC7eSOqqhCZ2g6Tt09rh3ZItaUl2BobiW7XvrVDOfMcImFJCDZTa3FS0+QgwKw/zIktQ3U72fD7/aCa6HXJMxhDWubn2ztmBD2vHkL+4hvJ2upDffU4Oo5+Da/As3QoUJI8w0GhnurYfj1uwq9qL85l75E75/+Q5n5BzKBL0Pa/G3zCWznYM5voq/+XCo1PpL68nLhOXQmMjCYqrR171qwgIDKK0MRkkrv3ou2AISR27UnOpvWUZO1unjibtW4Vqnrs29jrTV6YvH2aN6MTWp/By4vErj1I7NKDqoI8statxtpwZm1v0VhdRW1psUhWDsd16IQFIPs0DAtVrH8KW00kHQeNb7Fk5S+SRkvcsKn0OH8E1joN636aTEP+nBa9RqsKSkJ30ZskPrmC2CGXUbj0F/Y+OxDHz/dAdU5rR3fGEgnLv1hcx87Nn6wNXmZS+wxAqzOg1e//ZGb09iaxaw9sjQ04rBZMPr4kdO1B4Q5P9eLG6qrDJi8up5OCHduwW5oIT25DlahVc8aRZJnotu1J6t6LqsJ8T+LS2NDaYVFbVkp5bjbxolfu8JzW5qJxf2lOWE7xxFtVUdi9dSPewWUEpJ26EhS+ba+l/2Uvo5Gb2DDzCyq2vHbKrtUqvEPRnPcs8U+uJGHMzZRuXETWi8OxfnM9lG5v7ejOOGJISGgmazTEtu94yOf+WXvGs9ppDWa/AAp3ZRCV1g6fwP0rAurKSynPyfZMON69E5fdftYuy/43kCSJ6LbtUVWVop0ZWJsaiG7bvlWGivK3b0FnMB4wF0w4BKcVvIIOeMio0xDlbzrlmyBWZ/4fDmsw7fqc+uXyutDO9Jn4HZtnXsH2BTtIrL6B2EH/1+LD5K3K5I88+CFi+96JuvEriv/8BOvGsYS1647PiAchVizjB5GwCCfo79304cltKMrcSXlOtqeysaqgN5ial2jHd+zSWmEKx0mSJKLbHZi4xLTtcFpK3zttNvZuXEtMuw4tMu/rnPePZc1/SQg+9Uubi3b9iEZjIqDt6SmMpvEKpetlc9n9x6Vkbwyhvm406WN+Pnsn4x6O3gup961E9bgBtv1I6Zx3KX1rIhHte+B90UsQePat8GtJImERWoRYbnpu+XviUrhjGzZLE1Gp7U7ZDtuNNdUU7dpBau/+59Yn51PJaQXdwZPfE0PMrMmuPoWXLaOqMIjYFDvSaVz5J2l0pI75FbP//exZG8K6H8bQ9cLP0fnGn7YYThuNDjpPJLzj5YTv+IWin1+k/JVRJEx4DKnrpOaaWv824jeDIAiHJUkSMekdSe7em5riIvasW0VDVeXRTzxGVYUF7N2whrqyUlL7iGTluBxi0i3sq8VS1YRbOfaJ8cejZucnKEBUp4dOSftHE93vTTqfPwhLvT+rfrwZV0NBq8RxWsgytB9P1CNLieoxnMxvnsXy5dVgOXUJ6ZlM/HYQBOGoJEkiKq0dKT360FRTTe7mDSfUzl8TsbM3rSN74zo0Wi1J3XoRldauhSP+FzjEpFuAxBBvHC6F4lrrKblsVfEqdJITY0TrbfcQ0PYmel54D25LANt+n+Sp5H0u05sxXPo+aTe9QeXuTRT/bxjkLGvtqE47MSQkCMJxCU9uQ3VxEdkb1yHLMuaAQMwBgWj1+uYdoi11tVjq6lAU9/4TVRVJoyGyTRp6o6jwedIcTYceEtq3UiinsomYwJaf41GVr8c/orbF2z1e5ughpPZdSuaSPIpX/5fIPq+2dkinXrtxxD7cjbpvbmP3u9eReN7VaIc/4RlC+hcQCctxOJ7aI4JwLguMjCIwMgrF7cZSV0tDZQVOhx1ZltHo9Jj9/AmMikGjFb9iTkhFJuQs3VcdNR+qs8FpA43esxeN4gJbLYQdXKMm0t+EXiuTXdHIwDYhLRpWY10GDsWIT9iZMSk6sutTlO4Zwu5N9QR3LEBvjmntkE49v2j8bvsVn2Vvsve3j/DfuoiQUfdBu3FwFlSuPhnit8lxcDkdaPXnyFbogtACZI0G78AgvAODjn6wcHTFm2Dpa7BrFsg68IsCvxiI6AR6b3A7QXGC2wU9b4WUkQc1oZEl4oO8TsnS5oayxaiAyT/9iMc53XYcior5ED1ALa390LdY9eU75P3+MikT3j/l1zsjyBrkQQ+SkjyE2l+fIuvz/+AV8DIRI29B6nL1IXvezgUiYTkOTpsNrUEkLIIgtCBFgYyfYd0UyF8JgUlw4XvQ8XLQnlh5/YRgM9mnIGHxM6aCtAyD7jC7MCsufsz8kRdKAyhXQ4iQq0nS1RNrUHmk/fmEGM0tHpM+pBMRrh40rfLF3TcPTXRci1/jjBXVDf87ZuFftJGmBW+y94cX0cx4i+gew9D1ug4iz62SEiJhOQ4uh/2gHZIFQRBOWNkO+O1eKFwLCQPh0s9bpGs/Idib37YUt1CQ+0mSHtMG2LDuG265Mo2JgTUEG2xkWpzUK3pqnC42udPorK/gev8y9jQ2kOUw8lNDCBvWLWd+v2Fo5Za97TSV5WOqaYuNcsq+nEfkYze1aPtnhaiumCd9RXLVXtzrvqBo1Wzsy2YRP/gSdOc9BYZTX0fpdBAJy3Fw2u3oRA+LIAgtZcEznmTlim8hbUyLNZsYYqa4zorN6caoa7l5DZoGHboimWWpnbHojExpiEBucBMlV+EvWVAx8EqcyqSE4Uh/qxUyL28xk/aG8N7OedyXPqrF4gGoWLoKWRNITA/IXWvG67Nv8L/hqha9xlkjKAnN+c8RO/JplFUfkvvru5i2LCTiyv9B0tDWju6kiWXNx8Flt4shIUEQWs6IZ8HoD6s/BJejxZpNDDajqpBb1bLDQkpdHQAPDm9LTHUlbSpK2d0nnXWDRjJv4EXMHziWaxO7HJCsAIyIG0wbbQmrals4HrcLMrxwJZbjf8V4YlMd5GyVKXvtM1SbrUWvdVaRNcj97iLxkTl4BUWQ+f7N2KbdDvUlrR3ZSREJy3Fw2m2ih0UQhJYTkgoTv4OCNfDNpbDiHcicA7a6k2o2McQzBJDTwiX6LUvmojF4Y+47kjfigtkbGMzFMxawefvOo57b1ayw1J7ILaunUWFtmcJn5auXorX549+vLZIsE3jrNST10lJSaCTn6e9wFea3yHXOWoGJ+N3+G22unEzZ5iVkPT8Y1++PQlPLFX88nUTCchxcDgda3YlNghMEQTikuL5w2ReeZcqLX4bvroDXUuGnm2HvIs+k3OMU4KXDz6Rr8Ym31esy0GorkYOjGdC9Mz94Q7nRi/Mr7Az5YTY/L1h62PIPr3Qew32hFcy0tuHxrYtPOhbFrWBdUos9LI+AVM/kUkmW8Z14Ge2uTsLq1JD5xnJsy5ef9LXOapKE1P064p5cRcLISRQsm0H2cwNwz3sWrLWtHd1xEQnL8VBVUTpcEISWlzYGbl0KjxXBvVtg0MOeJc5fXQSfnw+VWcfVnCRJLb4JoupwUGsJJixh/9TH/r27s3ZUXz5w1+PtdnGH7Mt93/yC0+0+6Hy9RuaSiDSu/ulD2q5chMtpP+ZrK4pCxablWCr3TyQuW7kAXX0IfiOSDhqC0nfvRdp/h+NlsrDrxwJqp36HegKJ3znF6Idm+OMkTF5O7KDx5M77htzn+qIs/h/YG1s7umMi7r6CIAhnCkmCgHgY8ADctQ4m/QqN5fBRf8hacFxNJYaYyalsuRuRbekMVFWDz7ALDnjcYDBwyfCB/HrFBTxdX8b08Dgmf//rIduY++PvRFQUoazO4bOHxmNpqDima5evWYj9B5Xq1/aS8+JP5Hz1HdbldThCiwhuf+gtAjShkcQ/dS1RiTZyN0nseWwq1kULReJiDkI76nmSJi8hqtdosn//hLzn+qCufM+z3cMZTCQsgiAIZyJJgsTBcPsKz5Ln7yZC1vxjPj2xhWux2DauABRMQy895POyLHPbuPO4u66Ur8Ji2b4t44Dnv/r5J+wLZ2MZegFeoXaaqtzYLDVHvGZ+9TZeX3YrDfMbcfpUIp/fiBpiQ9rrg74uDFP3I1fclfQ6Qu65nrTLIpFRyPy1nOzHvsC2YA6q23Vcr/+c4xOObtxrJD++kPDOA9n785sUPN8HddtPrR3ZYYmERRAE4UymN8PlX0HSEPjuSti78JhOSwzxptbipKapZVYfVa7ZiU5uQjIeeX+i+y8YTnh9HY9tyULZ15vx68KFlE77gtoeA4gvWYi1Ssd5d11HYFgb7NYm5n75HQV7tgNgcTYybevrvLj4Oi74bSJ/7MrE1BSEriGYhohoEm++itgnRxP4n0TC+o84ptiN/QaS9OL1pI0LQUEic1YDOx6eSt3Ub1Aaz47hkFPGPwbDpe+T/OifBCekkv3lo1Cd09pRHZKowyIIgnCm0xpgwpfw/VUw/Tq4awN4H3mfoIR9myBmVzbRzXxyiwVsq/6gxhpJ8tCjb8FgNBh4KsiLWwKC+Gn+EkKC/dj1f+9Qn9qJkUkq67+3kNAnina9LsftdvHLez9RtTeavauLMIVuZLl5JWtDVmCQQQISw3SUBNTgu9mI4XM3S/rNYtDYC/AKiTqu1yDJMsYhw0gerGJfu56qeTvI2SSh3/oLcQMD8LpgNJLmX/wZPigJ05WfYXypP42/Por39d+3dkQHEQmLIAjC2UBrgEs+gbc7w9L/wegj704cH7QvYalopFvcyW1WWPz2m2jxJuCuD47p+AsH9WHqNzN5QSNzxdR3aIyM4+FHHgdLOeu/X07OqhK+s76Hyc+PquxIel1mpzS7mrwN0XRlAhPO78vI9tccMJl2Y9AyzHPB0XBy9VUkScLYqwdRvXoQtjeTkq+XsGeRDp/VXxI1Ph1j9x4n1f5ZTW8m6tInyZzyIKk7ZkK7C1s7ogP8i9NJQRCEs4xXIPS7B9Z/BjW5RzzUpNcQ5W866U0Q7RsXU9UQTly/8KMOB/3d/eEBXPPLR+hcTu564hn8TCa2ztsFgMaQRE1RHEVbo+hwXj3dh42ixMtT48pnsIXzOkw6IFnJ27OH0LlQb6xl8IRxJ/V6/k6blErMU7fQ9tIw3G43mV/vJeuau3Du3tJi1zjrtLuIqHadKfnt9daO5CAiYTkOh64uIAiCcBolDPTs2Lzr96MfepJLmxWHg433vIXGXU/AvS8e83k11XU0PvMimn0Lcuqr6gFY/9tXIHlz56evccWTXRhwDQy86BJ+mvsn9mX+KB0rmXTFBQe1V/L7KgB8bf5YPv0e1Xpsq1kURWmeR3Mkhv5DCEgMINAQSX2Tky33vUbZw1ejNJ5cAb+zkiThndgVe1PLb555ssSQ0HGQjn6IIAjCqeOyeyriBiV7dnM+ioRgM2tzTryq7OL7X6emwwTsVTUkFNYRkOZ31HOsFhtLr7yF2Opigh55m7nffMh3771Pt4S+KK5a4jqPRWfQERgaTWBoNF+u/J6aGf7UBhcx+dZrD2qvonQL8bXTcGovxS9Oon5vDNbnZxJ8S0+0cQnNx1VnVlP67S5kp4JGUdGooEWl0UtHu6cOvfT575rWViAZrXT6ZDIlk+8kLyOA4ssmkTyxLz7XPOxZtfVvofdCdZ15S5xFD4sgCMLZQmuAlPOgNh/Kj14OPzHETE5VE4py/P3DObPnUqPEYtA3YPGJ4ofXtrPhvd+P2mMxY/xlJOVtwzX5OXqMHkzMeZfhXZxB5spvAfDyNTe3oSoKft7e1BurCKiK5sPPpmP92x5ATY1lNE4djaxbg+nubvjefC3mwN243OG4S0sPuG7N5gp87W5cfgYc/gYUCRRAYzv68mXV6UT2i0ZtykMTHE30h7/S6ZlJeBms7JqWya6LR+DYcOxLys96em9PcnyGEQmLIAjC2WTc+xDXD76/Ekq3HfHQhGAzDpdCUe3xfVouXbOO9b9VYPJrYszrN3HliwOJNFWzeruJn+/4lrrs4kOeV/7+03TOySKqWw09dl7DvBduY8JlF1LvG4Vdq8E/ohs7l37Px7fdT/aqTXxz33T008u5894+qB0qYUMI7z3hSYpcjkbMr7UhxG7BMmEqwWEdcJcW01Sdjk7KRZeadsC1bSVNOFSVdg92QxPihRHQShJujXzUJEvS6ZAkK5rguObHDN2H0uaXuaROSMdu82bzk19RdNfFKDVlx/Veno3U+hLPcvozjEhYjoOYwyIIQqvT6j11WQIT4OtLoSbvsIcm/bUJ4nFMvN04ey2LvsjFKauMfOJKJK0Gr7BALnz3agb3Valx+vDDixvZ8ukfB+wbZN+0nB3T92Bt14asSyeTaR3E7oIJ/N/9y9BLAzE46/GKiqf/lf/B1ljOL289R41FIa8ikh9f2YG8LRgAr8YAPv3yZ6o/7A1AaVxv4lNGA6AJj8Qnbi9ONZGmmX82X7tgaRE+JY04Yn2RNTIa8/7ZDr4uhZ0vrSPj5bVkvLCGjGdWsePJlex4ciWV2/ZvAqjxU1Hd3ge8F5Ik4TvpP3SYPpXYtm5Ksn3YfOVt1H/y9DldMbdq1zqCEtKOfuBpJhIWQRCEs43BB676EXQm+PoSaKo65GGR/ib0GvmYE5bKwr1s+HMDdgVq3FH8+t2aA3on0icN44pn+hJqqGH5Bj0z7vyGhoJylNpKdj7wJBlpN7Iq9F7W/pHG/Lr7CPCqpDZYh9MrAn1AJ0o2/E5qz460iQEJB6Mm+HHtM13AdzsqYDd5irhtsK7mbpOn4J1/4foDYnQ3eOaSFOVEsf251WQ8thz1971YNTLJN7YHIGFcMpwfjzrC02Pi1+DAr9aOZHOBCqpOxtfhpvK7Xex8aiW7v8jAEO+PbAzEUXhwD4rs40f4a1/T8bW78TFb2DUzn10XnY997bxjel/PKoqbhsIsfFJ6tnYkBxGTbo/Dv2jKlSAIZzrvULjmZ5gyEr6dANfOPKgbXyNLxAV5kV1x9GquLmsjX77/Dd46DWUh9WgqnZRuCOeTvX8w/p7ehEQGAuATHcJF71/D1k//YPUaP75/ejVt935DYFUppO5vT0Jh4v8uQdJ4bjOVhe2Z+uBtTLnvOkDl/DG9SR7p6TkxD87nvbJv6akaaBtwIavq5pJgCwPKCHY6aMjagU9yOwDcDs/nbG+rikXnxq2TaQowknJXJ7RGz7W0Ji3Rg2MAyK6z42pyEX1eHNGh+5dlb391HVKjE53djdeuauqifNDjpH7xVoKvPnQFXX27HqT8OJfG798ha2oFW575hqjYD4h48SPkgLCjvsctxe2wU7NjJ47GRpwWGzovI3pvb/S+3uj9/ND7BSBrT/D2Xr4TXFak2F4tG3QLEAmLIAjCaWKtqad8bSaqWz3oE9BfX6qA1qjDNzkS35ij3AQDE+Gq6fDFBZ4KuFd8CxrdAYckhhx9TyHV5eKnpx4gQEmk0bsEm9OPlB6gr5Mp22JkzbydXHBtvwPO6Xjz+cQPK2be8zPZknYrCe7l3Ph8ezZ9NZuNmbH07lTUnKwABEeHktJzLHvW/IRJ4yJ90hPNz1016gPi13/AM1veY03dNDo62/HVzd9RvORXfBY/guarMbgf34VGb0B1yyA5QdURd18XDEFHrg2TeEnKIR9v/7CnQFze3FxYVIC+yAlA+fTZBEwYjEavO+R5AN5X3EPHC6+n4pnbyd/uTdnEW0mZ0A2f6584pauJKjdvZuOPa6mvMuJGh6pKSH+brKDi+VqW3ESlqnS/fhx6P9/ju0jhWkCGyC4tG3wLEAmLIAjCKeR2uiictxFFUdCZDUQN7ITWdORS+Y76JqozC6jamgMq+KdGEZASc+iDI7t45rR8cxn8dq9nUu7fbpoJwd78tuXQk2QBKrcuZflHH6BaIwkMXMj1rCFHiUJKm8qsKdVIZifDJ/Q75Lm+iZFc/OnN7Hz9BVbmdOW7p5YTbPDUXDH6eWO12NHpNGh1nltN/AXnsXfTTjoE5qMqCpLs6S3ZO/NDzGUlTM4IID+imJGTXkGWZSKHXEyVlx9Bcy5m/XcP0enCJ1AdLpBcoOpwu4/4Nh6TuPPisfYMx1JuoWb1Jpgxl8yXk2n35J1HPE/28iHsla8JyFhD3hNPsvPnHHx/G07S05PRdRp88oH9TXXGdtZ9vYKGGh8kWUtMmkJMtxhMQYFoTUZcFiv2hgacDU3Ym6yU7CyiaJeZ4kdnkNbHTLsrxiHrju12b9u7BkNo3Bk56VYkLIIgCKeIrbaBgj82ED+2Nzqz8ZjP0/uaCe+xf9Jj+eY95MxaDaqKf1r0wclL0lC46EP4+WbwDoPhTzU/lRhsprjOis3pxqjTND/e2FDC/710J6HFMYCZjtHraKvZRoGUSKimDPPM4cRpnqDA2pEvHpmL6taiKFp0xgY6jHTRa+R4iucXEpAWSPrDTxJXkM/iDxeQV+2ZR1LeoOPHl95Er9dx7bWT8AkPYMafRQSZzyfK9DLrV39Dj77X4LI2MuObv4rgBSCVBuO4SIIIsNntvJK9hH7eZsblTIW3pyIpL4FqAkBqoVmYpgAjpgAjQanDWDd7OMZpU7DcMB6v6PCjnqtP70Xyz3/Q8OXrZH9Xw6bHphCd9Dbhz5z8MFFd1m7WTl1CXYUXyHra9teRNmE8Gr3hiOclj4OG7N2smrKAXSu1ZK79kt6XJRM1cOBRr1m+eyuRnY5et6Y1SOrfp3mfxerr6/Hz86Ourg5f3+PsAjtGuZs3EN+52ylpWxCEc0tddjGVW3NIGNsbWaM5+gnHqGJrFo35lUiyhCTLBKbGQt4umpYuJbCTBt3GV5BGvwq9bgVgfW41l360itn39CXa383erD9YuP0nKnO80Dq1BOys4YG2SwAo1rUh9MGllOzeQOSPF6KR3Myrux13l3QMJiManYbSLAcVWaG08bPSVvL8rnV1DSXu0jaAyu9vzWBzZQ4ufcMBcYeUuei//E8cOh1SkJOguFpC315H446VfP3a+0y47WpmfLkIh6WISf/7Pwpslfx3ySOUawvwV52Mq9FxefJ/kH2icZOAqmqIGRZ71PerusFORbWVugY79Q0O6pucNDQ5aLS60GglLh2WSHCAqfn42pxS8i+8ALXrADpNffO4vjdKfS1lT91BUaYWSWkgeVw6vrc+29yTdDx2T5/B5gUNyLKbNt2NpE8ch8ZkOvqJ/1C2dg2rvt2Ky24mNM5C33uuROt1mGE0SzU5T3YlYdKr0HHCAU/d+/0myuptfH9Lyyczx3r/FgnLMVJVlbwtG0XCIgjCUVVs2IOlpo644d1P6XVcTieV2/dS8Miz+x+UJCRZQaOTMGoaUZCwuIx811uHBMiqjB4X/nEWrhnxDKEhHch5bxhJ1Rup0OqoGPkM7XreiaWmlD1vXE4nzWYySEF70bOkdvZMkt089QuCdyZRG+hAV6fH7IZGk5bw69ry1udvHTbedlnlRJZlE1TgWYpd3zEBr/O68eefG9HqU3A5sug65hbW+xXwTfUU/F1BvND3Rd6dM4UyUx6L7pxz1Pdkyfoipq/IZ1dlI8UOJxbpyLc4HyTeubQTQ7rv3/154+3PoFs2g/RN6455KOXvHBnryHtqMjW2SHykQhIevB3joIuP6Vy33cqK16ZSWeiDd5CFwf+9HL3Pyd3TVJebTVO+Y+8mkLV2Bt3UleDOh5ijkjmHnE9vJ+HxxRAQf8BTImFpQac6YXE5nRRn7iS2fccWb1sQhHNHY0kVVdtziBtxapOVv1McDnLHj8e+Jwu/iy9Gb6jGXlxIQ42CBpViayM/9XGyKLqJOKsX3185C2/fkAPaKC/ZROX3E2hXV866lIH0uOo3ADZ/+19Sd3+OEx0rQi8kwNyH6J2ekvhVvlaC6g/81P+rcRcVFAGgdblw7Vut0t0tE5GShNeLz1McFUNkUQHr27anXH9gUbsvRnuSmUGa83npkqfw8fLmie9fZo7lJ1ZcvRzjYYZDFEXhwffX8nNRFT6qRLLZSJsQbxJDzAT5GPH11uHrrcfP14Cfjx5fbz0FRQ3cNmUdBW4XgwJ8GJQawsg+MTT9OgfXm08SPW8pPjEhh7zesWj88UP2TpmNQwrER19GzNXj8Lrk1kP2uKg2Kw3fv8u26RlURvQlvl8gHa8df0K9M4dTtXULiz9dj9ulZ9idnQj6x/1M+fMp8pfNJP7ZjQdNHhYJSws61QmLramR6qJCItucecV0BEE4MyiKQvaPy0i8dAByC95ojunaViv5N9yIIzubqDffwNy3b/NzF72/gqQQb7oq03i9aSbBVi1Pd/ov011rWFWyisd6PsaFyReSnzWX2K8nsNM3hLYPZDWfX5m9kYYvJ5FAATuV8/Fx3NX8XI5vDUENRnz3zSvZbnWzxncFqsZJrMVI34BwmmINpF04lq3DR5DdvhMT/+9DGq0O+i7dypXT38TQWE98dE+WBRWxIGolYUoo866b37xj86LNK7lv0+20U7rx+TUfHpS0ZObU8NS3W1jd0MRVCaE8fWM3dNr9739FdS0Fn15BuG0vOT3uod/ou5ufa7I4efKzjSwoqqZWVUCFcIeF+MYM7k3zpdf99yLLJz6kp9os1H/2Enm/b8SuBqOX6wgItKMP8EIXEIi9tIy6cgWL3Re3okXTUIb5ootJe/C2E77mkThqa/jtiZ/RalUufPPGA3bFLn9rFF7+gXhf981B54mEpQWd6oSlsaYaS10tofGJLd62IAjnhrw/1hHUJRHvsKBWub67ro7Ce+/Dsno1/hOvIOzBB5HNZh74YTO5VU38fEc/Mrct5Yn5D7Ir8MCejc4hnbm9rp6+mYtZF9uFzlfNQmfYX/m1ujKfwPc6kK2NYkSvj7mlxMa48GCmr/gDCScj7d0Jzl5PceEWCqMG0indF++mOCSNDtzFZEi7iJo1De3PM4iNiWfF9nIWl1SztMnKU8kRDO/lmUg8Zd6HvFX8Af8NuZerR9/UfP1py2by/J4nCW0ayFD/66isdbCnuokCq51aVAwq3NszgTvGtzvgdamqytI3rqJ742weCg1mmZeJjwZNo19824Pevx25Vcxakc+Mzbsp1nhzZeH3dNQ4GTX5efySk0/qe6MqCpYZn1L8wwya7D643VoUF2i0Kl76OvwijDT5d8T54w8EfPwN4YO6ntT1jiT/j9msnVFHt0tjSBje3/Ogy0HO4+1JGHcP9L3roHPOhIRFrBI6Ri67HZ3hyDOzBUH496rcnoM+0NxqyQqAxs+P2M+mUPP995T/7zWali4j4sUXSQwJYFFmOQCpHQYyKHMIvX79ja3xEh9NXsfdi+5mbela7pW0PBKTzoX5myh6KxX54k+JbTMap91C1ddX4DQE03D5dDpm1vBmTAhr8vPpKHk2yfOa+RBNkp5gLx0h+bPxiv8vqOUYU/2xZUaSTiS/jIrDkOGi7Ns1BJY7iASuAHZs3MuQblFotDI3jridnB+yeb38PRLWJlFhK2BJ5jyy7Hko3m6yis4jq6gEbyRiDHr6hfvTLT6QCwfFHTB59i/rZ0+hf8PvTIwMZ6fBs5w8PjCEspoGZq7eydLMMooa3IyIM/LdlhoatN6oGk+iVhTQlvCS5XzxyD0kBISQMnAIyeMvQ+d1/Et+JVnGfMmtpFxy62GPWX/+VWh8wwnte2qnHsSMOI8Nsz9gyywX8cP6eXpZSreC2wGxvU/ptU+GSFiOkcthx2D2PvqBgiD869gbLNTtLSZp3KHrlZxOkiwTeOWVePfvT8ljj5N/7bV0P/9i3tV2p6bJQYBZz8UDb2HxZ78xZp3C4uLxvPHKFFY3buPx5Y/ztLaBZak9uDdvBxHfTmR13EDMNVUkN2axe8IvdEpM5ytfC8nbdhMbvJIBMdNxbwzB2u8SYq+7FJOznpppxSgNJUS/Og63yUT2kyuIVCUkSyyNi0rQmzQYRkWRnhqILaeeHb/mseTtjQT0CgUVJm4exY6ordy24x6QwCRrSTBHMt67Gz9LjVgVE9tfufCo74XidBCy4S0yDLHs3Pd5013VjyveWEaRTYuCjJ/GjUOV+HiHG3S+dJdL8PcxM7/Ol1LFyIRnXmXLZx+zNz+bPbN+RPvrNBJCIhj21AuYw4++7PlYuRub8MrdhGvCnSc00fd4SBoN3c+PYfVMCwXL1hI7sBfq3oWoWhOEn7nzNEXCcoxcDgfmgCMXexIE4d+pYO4GEi46s2pX6GNjif1yKjVffw2vv8H72mXkDgkkYMxgokKTmDhrOws/fJzwj2eQMXoE/o/ezdIJS7ll/i0sqNhCmRLLzY1uBucupcruxY+V7cmbuYyt2XVcPGQo/awSFxino6qg6VpB2mWXYI7uQPGj05C9gvG/OBSNrzfL391MkioxL0LDrU/1QkbBZXNQVpnFzp13guQmfoRKozWAxDm3onWbAR035V7Ml+YviS3z4tm352A0eCrPNhb/zNwCO/X1NVgaGzCazJhMJvQ6HZKk8UwWlSSqSvMp/PYe2rmLyep2P1ROA8AkWwkyyQxr48tlfVNJjw/nuR+WMWWTp+BdpLaKK3vFc6VLy+rPl7NiZh3jX38XRVEoXr6Unb/+xM68vXx7z81c+9l36L2P/kG2bmc21duzCRvaC68gn0MeU712KxIqPr1Oz0rU6PMuQDP7/9gycyexA3tRvmE+oamdPZtrnqFEwnKMXA4HWv2Z+40UBKF1FMzfSEjvFDQnunfLKSTJMoGTJqHt3pXCm27H+J/bKZuVQvArX+CubWLYHS9SfN7lbPvP7cQ9+jYLZ8/k1Ydf4o9f76Gm1odNwFZNKN6X3UhNaSmGJXMo37Ccj7/+P4aOHsw9Wa/gr6nhQZ8N+AztQulrv6FKEXh1suPTz/NJ3T9/K2gS6D3lXrI+PHBPo8hAlYpHBuNCwRiykLnOnxnW5wU0ei2jEvqjXZDOtk9f4ZVXP2Dy43cjyzJpDSt53fwpvAGHm+2gIBGEilnVsa77a5RoN2JQVLxUf9pFmfjosnEHHP/o+L7EBm1h3ZL5BMpWYhISiUpIJPPH/6M0azcAsiwTPXAw0QMH027+PKZ9/CYLn53M+a8euVZL7vtTsbz7ChIqe582YE3ogs7fF7WkEDU4goQn/4NvcjSlP89BlrQE92h/Qt/r4yVptHQYHMLm+XbKVy6hqXgPYYOvPi3XPlFn3k/YGcrldKDViYRFEIT9ajILkYxa/I6hIuppZ62BV+IBz419+HCo3m2mYsluqnt6hq60EeEkzZ5NxC8rWPbyNfgFrKFu7BX0AXZ30ZOlGHC7JUxff8YF/3mM+lGj+O2/d4PbQZ9XPmF5l2tYFdmeBxvCyHzoI66mDRqvIoKuuRLV7VlxYzPGghPKUi8gvGcMblVGlhRcu/5Au2IbYZtL2RWZy54ZKbgdxTR0q6JLmmc15sjhA8jfvg111WzG3KtQ6xVOgJzAzfuGd3aH9Kcx8RLcdjsOlwuHy4mqKMioeJl9aNN/PH2DQtk4fSYByDjRssKygsqGSoJ9gpvfKq1Ww7XDu1Kx6jc0qkpUgmdxhXdgEJX5eQe9tVHDR9Dht1/YmrubDmtWEdXr0L1ruV/9huXdV6hNG0Li/TdQ+ft8tCuXoFQU4Q6OxLR9OWXjF1CkMaJ126iP6oR3yOkriZ80bixbFn7Fxu+W08agQvKhN308U4iE5VipaouuhxcE4ezmstqp2p5D8vgBrR3Kodn/Vmn2wvd4d3kpxYkdmHxDAxXP/hcAa0kpmV27Efjx27h6rwY31Kcp+O6SMeXVQUwoAKVa+P7N55uX93aO7YZpy16eXPsFT/e6njUR6TSRhKJI+A3qS9HkFahOBYAoNNS6FDKCBlCXt29PI1XF6eqHpX0KFRlbICMav2gXtYUSv370AZ3ee6t5WfhN993Bq/7x7NylEiZbGdU+mYGFn3KP82surVjCMv9YBlz14RHfihpHAyZJQ4QhlipnFSuzVnJhl4PnwOg1GqodKtXl5QSGhmLy9UNxuw7Z5qBnXyL7hon8+darTPp6OhrNgbfTup3ZNL48GWtCd7p/9yZ6k57wQd2A/zYfs+ej6dTNmoWhXXt8+nUnZWSfA5YZn2qyTk9qL292rorC5RUKvhGn7don4rjuwB9++CEdO3bE19cXX19f+vTpw5w5+ysPlpaWcs011xAeHo7ZbKZr16789NNPR2zT7XYzefJkEhISMJlMJCUl8dxzz3GOrLYWBOEclTd7HfFje7V2GIfnHwu99tXyCErmAsfv9C/+AnPfwcTO307wuJ4kji4j4bwyPpzzg+c4DVieeRX7bX2IqG0kuMFCXGUdI7dlE91ox6UqDO4/jGH/e4aQ73/F4h3O02s+p3NlNpcqGiTJRf2fBZ6Jsh2CMXUOwXtAJMsaPbsUNti0WOwyVodMmakD1ab9uxeOuuVj4i6/E5+qbO599Rv6vrSA9xbuAaDez1OC/4cHRnH3ledhNYfznPkB1vd8mD57fmBP0e7Dvg2V1Vn85ihjiFc09/e7HwD5MJsQhUd4btjvfPABebszaWxsPORxdoudr555AzkkkWrFyeKXXjvomNJf5yEpLtKmvIX+MJtdptx2Gd1nTaXDqw8RPW4IWtOx7zfVUmJGjESWzDgSrjvt1z5ex5WwREdH8/LLL7NhwwbWr1/P0KFDGTduHBkZGQBMmjSJzMxMZs6cybZt27jkkkuYMGECmzZtOmybr7zyCh9++CHvvfceO3fu5JVXXuHVV1/l3XffPblXJgiCcIoULdlKYJf4M39e29AnQKOHz88nsXET59vnov54PbKlDO+rHsHg6+Z70yOMVq9hwbKnKLako1Q9wJZUI0HfvU03XR3pRZVoFZX0/DLumvI93e723PSDO7eh/cLZuCUtbxrDCJZ1yJIRyagh4rFeBF3VlqAr0nCnBKIAyTHeXP1/VzDx0yu54tOruO5/Xeh1ZV9C4j0F7vas3cL4i0aSZ4ohYNtsymoambmlmDqLg8WZ5Whkibggzx44iqqikSU6Db2XJq0XJUsPfb9QVZW35tyCFrhh2Bu4VU+CJB/m1jdqzPjmf3/+7XcUNVg41Efn2e9/RU3RBupqcgHYuquMutyyA46xZuzE6hOJT2TgMX6zWsfan/LQ+ISTcs1NRz+4lR1XwjJ27FhGjx5NSkoKbdq04YUXXsDb25vVq1cDsHLlSu6++2569uxJYmIiTzzxBP7+/mzYsOGwba5cuZJx48YxZswY4uPjufTSSxk5ciRr1649uVcmCIJwCtTnluFWXAQkRrd2KEdn8IErp0Hfu1lzwXyucT6KWrIN3ukMnwyi0TWK4WpvIpG5w5pA5Kb/UrTnIdqsnkfJ/+4i7u0p6G4b4mnL7aZm/S8HNu9rQnvXeei8/xpKUAm5uSOycf/wiL3e4TnWbGX1219gq/DUgzH7BNBn1IX0v9yTJGyY9QmyLDP8ulvwdjXRpW4Lu8sa6fTsPAprrbgVlb4fLeeaX9ZTVdiIKoPO6M3OtlfRNWs69TXFB8RWWrKJq7/swa+uCh6KuwC/oBTciidh0coHDt+oqsrmOat5/YO3DnhccrqQgIId2RTuyqVodz4lWQVkr58BQEz78+g55nZMhiEsem0+JUs2svP9H9n+ylSkratQ41JO4Jt2+mRvqqBxdw0dr0jFYD7Dk29OYg6L2+1m+vTpNDU10aePZ8JR3759+eGHHxgzZgz+/v5MmzYNm83G4MGDD9tO3759+eSTT9i9ezdt2rRhy5YtLF++nDfeeOOI17fb7djt9uav6+vrT/SlHBMxQCUIgtvhpGx9JimXDmztUI5d0hBIGkJElYVVSjkrxy2lf9FnqMvfotZ1Jxp9HUGPn8fiL7fTbm8jqTnpOEvuwb7tG/LHTcT7vksImv4hRY//h6o7XqTmwl9IevJztF5+FN73HOrc32n02Yh5yJPY9CqLFmQT1CaA5Pah+HsbUNwWADJ2uYFYtj21Bp2uETXUj4QOoXTul4JG54ek8QyHXDi4C+sW9KX7ntXs8knFovNGVVVkVEry6ikuqEcCmvZVy08aej+OXd+RN+NBulz/bfPLfn/e3RQoNj5texO9e98HgKJ65tX8fUjIZrOxesYiFu9aQ6DGh1DfYMKDw0jv34nfnn2fGkqZ9sw9h3xrO583lDY909GV/8yGrAhyHn6KgLosNIDDN5LUlx9t0W9lS7JbXWz5fhfmlAASu5z4fkmn03EnLNu2baNPnz7YbDa8vb355ZdfaNfOUwp52rRpXH755QQFBaHVavHy8uKXX34h+QgljR955BHq6+tJS0tDo9Hgdrt54YUXuOqqq44Yx0svvcQzzzxzvOELgiCcsLzf1xE3+vRtatiSogJM6DUye2tV+o94hnl7mmiXD26HH45fZzLixospLW4ka2MJoUvb4j3qf1hWvInllZ9p6LqIuLf/j/JfPsH+2WIy1wxA790Zd9Z6tDF90McPRJVlymWJNjtq0e2oo2pGDpkytJG+Js6QTECAlXaXXULG5zOxun3YXdaPjIJ6tv76E25nHSm9BzfHOurm65j/6EaurpuFLSqp+XGXrAFFBVVlpt0zfygkIJxFKRMYsuNTtm38lQ5dPUuWsxzVDPRPaU5WYH/CUl1axs+bviAnP58GpxskiSCnibuf/s/+a9ldOLX9iIxpT5thMahut+d8xdOO0ctEcve2qC431bU1gD9B6fVEP/E7prAwJJPpjF2o4bC5WPx5BjgU+l6ddlon+p6M405YUlNT2bx5M3V1dfz4449ce+21LFmyhHbt2jF58mRqa2uZP38+wcHBzJgxgwkTJrBs2TI6dOhwyPamTZvGN998w7fffkt6ejqbN2/mvvvuIzIykmuvvfawcTz66KM88MADzV/X19cTExNzvC9HEAThmJSs2oFPWjh6L6/WDuWE/DUHJLuikYVV9VyfdiWBCW7u3d3E+RtDsWZ+Q8ik/kRcmErB5gywhGC/YCIBbQqpe/lT8sdfiffdlxD43fvseOAJfHI2sX7gODr6D6euYxBDruxErCzjsrvJ21lB2a5qmiqa2FCh44KAF6jBh4D0p/D3WUUXNQ9j775U5BZQkWfD2Qh7185l1S9+uGQtBrM3Jo2KXF+DPdSBqtPjCg0nKDGZ0p1ZmOpK6aPuHwJKy54JQGPmXOg6DoetnhyNxDDvA4ftMrLXA7Bq7Xr87D544SY1LIyCLVsIlEIPOHbJZ1txSQZCOybTaUQXtNqDN0AsWrKE9bNzKKyLY3jvbJJztlO2+AvMNzzb0t++FlOcVcvazzNQLC46XZ2GT+Dpn+h7oo47YdHr9c09Jt26dWPdunW8/fbbPPzww7z33nts376d9PR0ADp16sSyZct4//33+eijjw7Z3kMPPcQjjzzCFVdcAUCHDh3Iy8vjpZdeOmLCYjAYMJzGvX3OjvxTEIRToam0GntdIxF92h394DNYQrCZFU3VfLK5gWEhYbwUoeO/rGFWZDwvbo3A/uFuVMcqJH0MkncRHf7r+b0cPOASsh+7AcsrP5Obuog77niObltX0WnHav5s3IvZkEr7PBNhCWloDRqSOoeT1NlTm2b1tCWwA3L7vEgAkKzm4ELDosWLMOfsaI5NsdtY+f2XzV/LgNPbH1XrqXD78NVX4uvrS+2A7jz7yoc0Go3M25OHSa+hq6OOzdEjadf7JurztvL8yodokmUig7qwpWQLBr2Bb+a/z6+WxYTbAzk/vR+9Bw7BL9Cz79MvDz1JVXnBAe/Vrq3VgMyulfXsXLkING7QKEiafRMEVMBmBGIZMrCa1Ctvovjl2RiK5gNnXsLidims/TWbksUFGKK96X9fV/xCDt576Ux20nVYFEXBbrdjsXjGKf+5pbpGo0FRlMOeb7FYjvscQRCE00VRFEqWbiPpsrNo3sphxAbrWFb7IoHFjbQPm0xMyHl8c14UP6z7g6u8ffjv5gb618XgyF3GnrJF5PaKod+IfhiD42j3yQKW3nItoUvXctncn/GpycPWqQ++FYU4dm+m/J1p5He4gPQJT+Ll7Q/A7m3r6ZTxCuuCx9HjvEkAuN1Q5NuToKJibPviGv/M/5BcTr749jtAZdI1k9AZ9IRExfDmm29is9nYvHkzAwcO5Mlpj7OUvtTm+bF0xh6c3YPZrjHSufBPmPonbmBOgmcZ9H93vA1/5UQqjKAbL9/4MXrdgR92o9LakZO/ifqCUnxjwrHWNVEdupKe8V2IbJdG7o4y7FYXdqsLl8MNKqi2auKlJYT2b0u78dcBoEgG5L/NeLRZG1EVBZP58DsQnw5VRY0sn7IdpcpG/OgEOp8XhyyffR/DjythefTRRxk1ahSxsbE0NDTw7bffsnjxYubOnUtaWhrJycnceuutvPbaawQFBTFjxgzmzZvHrFmzmtsYNmwYF198MXfd5dm+euzYsbzwwgvExsaSnp7Opk2beOONN7jhhhta9pWeJDHpVhD+nfLnrCNqRJezZpz/SH6ouBotoPNK55sND2KSXNybPoYreo1mUGUBN0hb2bJyI42JKsMrtUTdcwszR47nvJcfY9G3PxCzbB2r2rXHpzoX99Ax/Hd0T758/GECzBpqUkbSK+9LGl77iS3t7yd12HVIP99IpTaUjje93xyDhIrJ2w9J9RRk8/LzJz6tLQChAbMpa7IRGB6OX4BnOfD999/PO++8w8KFC5E0Ev4BgVj2eHoGAusbeCUmia3nf0mitYTF8+ehovJ4eAxu33g+3DaFOkMdqfpEMu3ZvHzFBwclKwAJvXuw7M+vWfbx54x5/lG2LFiHG4WeI3oTEB1Ch14Hr/Yp/vhyQkrmw+jc5se0jkqc+v0VdL98/E+cFn8ufyqJ4Ii4k/7+HS9VUdmyIJ+cWTnIAQb6P9iNkJhD72V0NjiuhKW8vJxJkyZRUlKCn58fHTt2ZO7cuYwY4SnnO3v2bB555BHGjh1LY2MjycnJTJ06ldGjRze3sXfvXiorK5u/fvfdd5k8eTJ33HEH5eXlREZGcuutt/Lkk0+20EsUBEE4MX/19JoCWvcTcktwu/YXaetp8WGDNoxPNzxFVl0OnUO7U97QSKYazqa+4WhUCB57GfKPP5Aw+3v2zPuJOEVhbZ/+1DQV4+w3nIdvuY2Sn5+nxuHFxBsmEjnkKopz76b0p0fos/0p2P4UgUB99PVo6+tRLFYaa6rwkpy4nS6sDfWYAwK57aMvURUVxe7CbPCCJhvTp37JVTfcDICs0XDXXXfx8tsvs2DeAorNJaQE+JFR1RYfWeH85AQgAYAFa34nIyADqWgL2iItFoMFX5cvfQO7sMeWjUanO+R7s2GaZ7l2Y2M1AFt3bSfaGEJA9OFXz0SW/AGA4+kkbPig6AIJ1+4mo2woi1/7CnOQHafFU+Jfpz990xf+0lBtY9ln27HlNRDWP4pelySh1R08D+dsclwJy5QpU474fEpKylEr2+bm5h7wtY+PD2+99RZvvfXW8YRy2p39n60EQTheFVv34p96FtRbOQbOvXXM2fkB7/quYXH4D9iwIQGL93zM4j0fA2AJ+5RPUhK5MMkzAbU8/SFudEdzzZ5fyUhMoZEGIi0S3QIryd72B6awdGAthkBPHZbI+FQi//ML2RsXkDjzEgB88z6HDz/3/BtAhrqaOkCiqcaTIOx48Tf8GgMYQmeyjQsprK3llTf+1xz7hEEXcsetd3DPF/eQWpfKKpdnyKfQbiThkVnIXjn4RXyPM7geWZUZ4z+GTdWbcCtuUkwpuNwuJFVC1hz6ltd5wjj2PL8Gg8GLypwyih2VjOoy9LDvZUVGBq61fhhTvNGHxiJZSpEd5TgdMtZyDRWWKCqy9h/vExB62LZamqqq7F5Tyo5pu0GvoeednYhOO7OL1x0rsZeQIAjCYViLqgkbc2YX/zoWzgoLVd9nok/048+iDlwX0oeyhp9YZ9tMqaai+bjE0u95p6KRaZtj6GcexsoVGyk2hbPihqcp8ddhXDadyPJCtv6+mdxN27hw4u0ATH3xda5/xoeAtB6edroOgy61OH99lbq1ErLehrlPElULs8hr3Ilp1HjYMRX/ME+ioza6ceLA0VlihK0L+qBAZFlDfW0dS/aswe1WCAsI48ObP2Tc1zfRlNuLiIBq+vn6EBAYyPe2T3ACPm4fPjv/M9Ii0w54/RdOOQ9V4rDDeuHpKQQHxJCVv5mCGc+TnLKbCs1m5sx5e98REvz93IICgoO9aP/0CkwBAQA46ivI6jmQ4IdSuPmaXlgaGvju6fVEtK05aJ7mqWJrdLLsq5007qjCt1Mw/a9Mw+B16F6ls5FIWARBEM5h7gYHZa97qo0HX92WuM8bKLB589qVb5CxpYBZ8z7gu6A/cMsuGqQFNCjgW1RNSbWbJI1MglyNoVrijYvGc3VxB9429eMF5xSslU2EdBnOyLFbWDJ7KTNfeYKJb3yBO89O1fd/rbjpCWjBBrtyy6iv1ZFR2whfTQWgtqyEj+94iF6G7tT7N9HpigtJ/Vvsu5ZtgT2QuXMXluxqvAxejLFM4iMgxs+L1267CICANU/x4a5nkDXRLCpfxPKq5WglLRpZg4REuauKQOuhb9wFe7NYs3QJWWZQwjrSIX06iqJBUcJRVJXmGYzNExlVjEkVWDW+zckKQO47nhoupqR09Hozy+b9juL2p99Fp2dzzLyMKjZ8uQNcKh0mtSWlxxm4g/hJEgmLIAjCIVgr6tD6nv65B6dKTp8nyFroZLTfZWyvbcvmjAhc32XTVzqPLyv7Ixu2oIv7kfMKz8OgGLCZFf5728O8+sk3yEUZPPq/Mu69aBCrvsinUnXiLYGs1dHh6keI7DyAqc+9yE+PXEP66EsJJH3fVfffYqJyQnCFWZHqAwAFrV6L3hQEqMiSEUXyPihmndGArErsqsymgz0MMyoXE8jHNNBfb24+7o5el7KrqohFFf/HB1t2HvzijaBzehIWp9PJjg3r2bx+LUXlFThkLagK3t4+hESWo9U6aZPyFTExPQ75PjqqS1m2rh8hXt0OeNxdVoE7UCZs8NXYmhrZs8pIZLsyQiJHHtf36XjZLU7W/JRF1dpSTIl+DLguHe+Ac+f/7d+JhEUQBOEQyjfsJnJop9YO46RpfPSE3+YmM7sQgCSv90gCqsrAkD6EqX5jaNhiQgnowyCLDwalCgBjk8wfs37l2Xuu46Of5uPauZaZ380gQEpDr4HGYhd/Tn2Ykde+SlD7fmiCvCiphk6LXyND1550+T9UaGuoirYg+ehI3RZKoiOekOh9k2m1+4ZJJDArKlig8LHlngmDqoqkkTGocEfqZQRf047CR5dhSPQj4MIAer6ZwVd7rVzVUEeQjx8A74y+l3avF2FriGf67b1wq27cihuX4uLeOXditGn46YspZGTnosgaJLeLQJORtLZp9Bo8DN+AAGbPHoPNFnHYZAWg8Of/YYhy42/qfMDjrpIK5BTPXJFZH/yPprLdFNT68OndO/DyC8AnKAT/sDACo8MJiQknKCYUrfbEb8GKW2HHsiL2/J6L6lJIvjiZDkOiz4nVbIcjEhZBEIRDUNxudGf6bszHSOsTw6AVVTT4GNiR3B6bVy4A9qhFTGQRE/uBS9VQkNORsvSJ3DVyON988w2ZmZm8+OKLmM02tJIBcDM0vIiB3S9m8RdfkrNhB+yr77l75LVE//gZc4rTABdT+r/Cbp8S3hn1LT5YeLr+NbYb9nB9+UX0UIdg0OsBFRSgyoqiqsh/K7+lCTbgKrdiy6ii8NFloIKklVHdTh7CxLWqnTum/sS3t1+HRuNJfu7vN4YXZjSybHcN9w0Y3txW34p+BDvC2NZYQIiXid59+9Cxd78Dvr+1tYXo9JkYjZOO+F6a3Svov6YGVX0c1+qncClmFF0YEVIJVT46SvM2kr9pPUafALx8IrE21lCRV0xpVj2ozgPaSuk1ntF3XY1Wf3zzTAp2VLNxWibuKhsBXULoeUkKZv9zs1fl70TCIgiC8A+2mgZ0XmdPyfKjMviidasEqKEEdP2F0e8s4+froglt/JGsmp9xa2xoJTcJiZuoWJPAD7tX4K+XsGsN1Ln02O0KCYnriQ1MpU27joTGDGPbsjlUFdRhc1gx6k28f9EF2MeO4oc/51HxxXs8Nu5dJi27kTv/uBQAyUvCrJr4OGw6A/qPoV3K/t6rwkeWIf/VMyDhmS+igu+YBOyZNahuTybjMywWOUAinCL+E1PAc3lx3PbFND68bgJajcyNPQfwweKv+GChxE09LXgbPNsoBDvCPE37w533PXbIt2h7xhdIErRPP3yFdQCToxyH3oAz+HKoLkBqKka2lxGc3ohZkvng4ScBiUvvfYCQdp2bJ9wqikJ9eQ2luUVUF5Wzatpb7FnzE++u/5N7v/oaWXP0Jce1ZRbW/LCbpj01GKK96fNgN0Ljzv4l98dKJCyCIAj/ULZmJ1FDOrd2GC1no2eSK8OfIiHYM/cjuymIrt2fI5rnALDX7CI7YzlDEuooKSvHanfi7arCC5mYtrvxNlhxGmewK3cGu3JhQU0U7Sp9ef+ay4jQ6Qn0DUIfHIt93+RUg6rnrq738e7axwFYNGERXhi54tvLeGDpf/g+dDr+fgH/jBTZR49S78BVYUUXbsZ3wIHLyt0OKwDnpSagJpfx4sJgrv/0O/7vxssx6LS8dFEPbvsihwdn/chH4z29JZOfnMzkFyajuA9fQb2ubgGQREDA4Qu8qYoLr9pqGjqNIODCdw94rvaLHpCT2/z11889iawoeKkSZr2BqIRkBj75HP7hHQFI6JTKb2++RUNl5oErkA7BbnWx/rdsypYXI5t1dLwunaSuIef08M+hiIRFEAThHxS3gtZwbgwHsWMmLHwOBj0CHS7FBET6GcmuaDzgMENAGm37718OXPfaa/jxHGt1n5O/+kow66gP+B6/+FXEJvUnpv8mVntV069Jh22Hlr1NFmyVxc0339kP341LC21TY9gZV8D9nw+gbXAiPfwC+aFpC+NnjOLnUd/iExxL0KS2VH3pmSyr1DvQBBpxV9s4FHudp3aL1mzmxl43YDJ8x5NzvLnmo2+YesvlnJ/WjjYxW/hzk56C4WXE+IWhkTWggrHBiMPlQK898HvrdFoxGvMx6K884ltpK16Oya2iie530HNqUT6aYonBcj0BV/2Hsu3bcFot1FdW0FBfy6Y9GRRcdwXj3/wAc3gE637fis7Yk4CIHkx98FckjRc6sw/e/ia8/PR4BxjxDTLhtLvI+TMP1akQe14cnUfEotWf3QXgTpRIWARBEP7G0WRFc5xzCs5YG76A3+6FxMEw+JHmhxNCzORUNh3xVH1QA0qDkazKIGqsTgKdCtUlF+KyBDLqwidJT4cs6THyDD8QMUuH74jzqVywnLK2A8hLjsFWqkOr2ui9pxqjw0mFXx11xnyKpFyQJcpp4qt159HWAFqXH5pefmgdfmjt/mjtvkh+ehp2LENX6oMsG5A1emSNAWtlGdujI3E7rAQXricqOY2bhm7k/xYFc8G7X/P0pRdw15A+3PNlBndN+5npk65GlnVoQjRQBlr5wNvero3rWbhoOqldwO74lsINnYjudukh3xN77p+YAGPiBQc9Z6pVadIb6fT572iNPiReMO6A53dP/4E506by8T03YVRUHOa++Aa2xTfcD7fTC0djA86GMqrrFarU/SNjkqQQmZhCv6vS8A44h4YpT4BIWARBEP6mZGUGkX3Sj37g2aB0m+fvwg2w+w9IHQVAYrA363Krj3iqHN0OOc9GjdVN5/aB9LurM3O//I7stT1orKvC2y8Iy5q1BOzVICkSckwCBtdcIuIjqdRE4DSEAQ1gy6TTHgMQygUTL6TNhTdRVbWLNWvvRWfMBgn81aEocgN2qRybbx5ufT2q7ESVXag2F6pm/2TV3YZUnkl/EVzAnn0Parshd7OTtVHHNR9taD52c14sXb8fgISbMRVj0KDh+aeeQlJVZFXFKUug0SK7ISg/jCBzFZn8l8yF/0VukFE1KqpBBQ2gwIA1nhVUNRuW4NtBhyl0//CRVufCGN8TrfHQe/W0uexyQjp2YseP39NYWUlVUSN23Fz6yPCDjnU53RTsqGbGlCVERUVx3l2dj/i9+rcQCYsgCMLfKA4XOm9Ta4fRMsa8DgP+A2+0hdkPNScsCcFmpq0vQFHUw+7aq0nqSONSzzLdzdur6Qf0HD2Yvau3smbOAoZdMQG50IJpowY0GrTtOwOg++0zvNpMpDYihDs/HscHN9+FywqqJLF19QIkPz/0Ji8KN7fHGG0kOmYHhepuzr/gRzSHKZ2vKAqq047baWdr1iKogXuDy+mmDWBSqac3TAk0ENjTyI2xiVidKlvzM5mvCeR2zTAizRqafBRCNmZi39KI14B+qDojFXXV5BfupXNQCLr1PYjTBdHQ8CtO7wa0YaEYktqgc/kiyTpQVdyuzwA3YcsegGXQ6DbRoI9A0foSpXdTWuXC6HSg0e0fclJsdpQmK+5GK0bVRLcrbkIXHsiC536h1OI85OuVJInls7bj4+/DRff2PIFv/LlJJCyCIAj7uJwOZPkcmx+wxrNPEBe82fxQQogZu0uhuM5KdIBX8+NuuxVZZ0CSZTRxbdBLjgOaCgiOILztfLLW+DDwEhuSRcHdNYD2364EQP7mF+q27aZxbjlBrlLWzZyJtT4XAE1sHBnGYDKWeOaqROkkBre9nSptCT/UbsS5/CUuGjT5kC9BlmUwmNAYTLg0ngRlbGQiS5btAb8Ixm1cye8de2Kqr+GuLvEA1LX1JXV9AeHew7m4hydRqyt7kuIfp5P61efI/sGHvJbieITdvfugOutpu+2zA5775OtdRASH0v+ua7FkLsddsAF93V4CmnZgkzT8mm/FdvUlDIu4iiBtMEgaJM2hhhdzqLf6YFQsh4xh5YzdVFZWctV956E3itv0X8Q7IQiCsE/JqgxCu6ce/cCzheJGWfMJMpD/yc3offxQJS1JaJhZ3oD1ZS9KzW7cWi8ktwM/Rz42yZum0F7UOmx0lBvx0pdjcYQy98vv8Qk0ERjhS0mGD7O+uZO0LXUALLzyPLzc/qDTI/n54tL2JcjXTfshQ1j6zSeAFnNgBHU2J+m+TaSlpZJ+3vXIGg3WsnKm1nVjuruJCxXlqPvurKrxJAA7F+TwXIhnL6JLyyqp37yBrUmJZFfXoGr1GPU+BDnr2Vhbxxi7BZfLgWVf8Tykw19D1usxpqVi3bzlgMcd9fU0yNAuKoaA9EEEpA9qfq6prhF3Yw39flvAgkU/sq1mGSM6DEc2aJEMOhoMe8gP/RxZMRBYOZQQ20CaMh3EhUYedP3aMgvrl2+j38h/15LlYyESFkEQhH1c9XZMIefQTULWUNT/bWp+mYxB48Je24CXtwlXrgXdWgMuXRO2dBumNlYkSaJJDkSnWAgqW0i07AAJ4mJnkFM1ktxNgbisZsBzs2/MSQE8PSthu/JwOUvQO53U+wVh6TKeHCsov2xl6G0vMG/q6xRb7eQER2GOjaJXv4HNq4k2lHnmhVgkMx/tmsMd7cYc8SWtdHtqqtwdEgJA711Wdtf3p7aNF1UBRvpuydt/sM6XKfjy/EsRGIGKTWGs7vcoix9ci0Z1IqkqGQaJRV5utG4b8r4Ng6Tg0TB8FPL93+KQtMiykYuqizABa7ZtYM3lnkm3stYHvSkQW0MeIGMK8KHNJTlobbWoXcewreKeA2J3A2UxP7By9Ui0aiNx/RMOen3Lf9mBl5eJriMOv7z630okLIIgCIC9rglZf+79SowZPIHogZeybdGfzPvkPbQGA/227cWMnWovXwI3S1SVhpL01lv4d+7SfN7W53/BxwVq1wfpHzia1M4X4XTaqC0voaaijODIqwl89hGWLp2M0/Ut4ARVJWlzKdosGy5kcleq5GLBEp8IwNz2vZgLvL4xG1lx4+tyoLjdaPVGuhiLebYslknJVrz1h59D9IBzNgZpA2WL78ZsBT+LgorC0K1W0gqd1MSUoFpqCBw4jFV19eS6ZT6PvpSuzmJsl5YT2+Z5KlbcQ6QSiaoqzK/1w66RmRDYhKooqIqKq6kRVVGRfXz4wuIp/R8eEICsSUMb4Etl4Q5UxYnisqK4nUiyEVljxByVjVeIDShhxz+SFaWqHdExlzAvR2WlWcvQaonwngduUFieV8/undmcP6EfWt05NjTZAs69n05BEIQTULhoM/FjerV2GKeEJMskdevFWstr6OotyH37wILFWLUG5If/A++8R9HEq8gK9Ed1OpHcCvqgdGwD2gMQE+cZ/tDpjIREJRAStb9noGvH21m3bBGKuQS/ehfxDXXcGjYRAIdiYm5MXyqLOiLLCmO3LOe3Tv0JttczzmykWHFTpigkaZy4qWQdseSX7aVdTPvDvpaU2Bh8i6cQOzqK3TMW4TD4oUoqGlUmutaNUVeAwWnBnZ/Fr8MHMHLVElaldsUnoAeB5f8DoP2oONp3vwiAH99ehbmklscfu+qga1kdLr6dPJc+vt7c9PgY4IoDnlcUhd+X5vPkHzu4Mv17IiMqAahoHImv6sRgWg1aT6E7NBJte1/PjTlLuD6/lKywIEymA+e3LJuRQUCgP2l9Dh4qEkTCIgiCQMXWvZijgtDozt1ficX/9yn99hR5vsgpASA7MIrhN9xE09gL2fXs06gFhcheXqAo6Davg2/WkZE/iCmVi4lIMBHlFUDfkES6BSWg27d/z+apA1E6qMSvcBFi6AYspFHbk7oBV+PcPpPQsPVcFlVL+uiF1NTk4716Lt8bunFJmpluIfvnCw39s4xU7Q4KM58iZ6eWKlcPjHpvRvV7CR+T3/4Xonqq1Y7pFceWecVYzcWkd+3GjvXrUGUZw76FN5oNq+mr8+MT/d3gBMqhQtOJEPcWJPavjFJUlcPVi33/nfV4SRK3jzn0vCZZllm0rRS9Vxldo1Y0P+5nWoT+b0uxHTVhDB/7A7//+DOT1rhxSxoeuqPvAW0pikphfjEDz+tx2JVb/3bn7k+nIAjCMbBU1NKYX0HCBb1bO5RTpmbaNFxTvsD38ssxTbgUZ20NKzbl8GauF5OcbswhoXR794Pm41VVJefyZ6i1zafblh2kZuby4LNPUNPgw6vlDZhYQ2d9Bf39dERGhhHuLCHJXQuWhQBI/nFEDboWBl1L6Zw26PZVlg0IiOWlEdfw/bIdrCzNoFtIKiuLa7l9UzZlXvFILjfl0iT0rtnoKSBIzmftqrloLUNRFAeKaiXHbuCbHU9RvXQhGkdXNIpC+Opahuhlzk9O5o+srObXEVsyi21xnejAFiLb/0BXOZyNWwcd8N6o+4q0/V21zcn/rc2lu92NJiaQNubDbyyYV2MhRPX3vM+OBHKrOvLetqEYNTaW3pmAwRiAX2Ai65YvJWuFDR9ZR5vRkQR7H9hmfYUVt1MlOMb7OL+7/x4iYREE4V/L7XJRtHALSZcNaO1QTgl3YyOlzz5L/czfCLhyImFPPIG0bxVOTFQ61o9WkVdlITX8wGJnkiSROO1p4GmmvfMhbT9+n22Dh9Jor2VV6VaWVpWyulHPG+XBfPmWlvBqPW/feiVTUy9hqpxL+vDrm9tSUZHYvyrHqDUSKDVQYHficCs8k5FPmZeMXGzBUOvg6jsn8+OMdL5cX8E1ff6PYFM1DmkxiqRBUQyUVXajyhZE9y7BuBSFjK2llCk+dJA19Jw4kY61teStWcvsvdOJty8jaXcAtIHiysWEBU1ojuovCuoBe/IsKqzh6owcNBqJnskGlodqmborh6acXLyc4JJUnooIY0KXKABKrA7aBAYzbOheAIr27uWLTevALRMa2Q2AbZs2sPiXLIJlM77JJvoPPzg5rshvACA4WiQshyMSFkEQ/pUURSH75xXEX9DrqEtpz0bVX35J2YsvIRmNBN12K8F33NGcrAAk7tsEMaey8aCE5e80eIq+AXgb/BkRN5C/FrDs2pOJWlUOSHyWNJ4yYzAjCCF4wXL6KWX09zWhlYMJ/EcfRpimiSI7JHy1EnecN+1tkLWtBhVIeOQ3VAz4EkD5+jYMlxYRpDRR4DeImPtnsmHK72hUFz9O6MZ5L87AqerR42Kb4ub8qirMoaG0HT2KJOcQcl+Mp41azk+JobB3IZtKPwRApzc3x6L+Yz/EiXvyQC/TwWRgndYBqoqXVsbPqqJqJXabJFYVfoJf4Qr8zBdRoSRwfvD+9qKSkhgevoZfK8w4bTZ0RiOZCwoIxgvFR2H87QeX9bfUO1j060ZCw4Iw+Zwje1idAiJhEQThXynn15VED++Mznxu7s9S9uJLAKg2G1UffYx9VyYxH33Y/HygWY+vUcveiiPvKaQBlMPsClw35Uv+WgQ+/bdpDJx4B2OaCkkyWVjuNvKILQp5y3Noqu303zOF/smBXNp7EH4aiQX2NhDnaddhdze3Ocq8hz4pYQzq0gGlxh9d8H3Uf3kRqtvlOdat4Ja0tHv0ZywY8ZMsXGAsBhVsDQ2YQ0MB0EkySYodJGh0+xNtzmy+xsqf9zD/I8/tb66vBUnTRO/3rsJhldF0HI9bH89mq735+B62Et6+eBQWu4vEldvxMxegJYcm3uSBnonU2wP4+s94TKZIfM3R4LWJq9uVsXL+LOzl51Ff4sToJTHxqcsPeg9dDje/vL8Kt8vNuNv7HPF78W8nEhZBEP51cmavJrRHG0yBfkc/+CyVtm0rVZ99TvXUqbirq2lcvBhnURG6KM9QhiRJJIR4H3ETxMK8AlI/eOewCQv19c3/dCxfARPvIMWl5ZFhnqGX+oYaOixYBcCuSm9W5Gt5Z+kiIvp6gWlfm4pKrlZtHjTKs+h5xanBNXczKCputQS360YUl2ei8PR8z5EWjFytmUcXbQEZ2m4oTpj+9pNkJjXhq9Vyefka2kme7pOq0mqi/1bWxBy2G29TT1RFZeDubazv8ytNhnIwa4ncYcMeei3lkdEk5+wkK6EtP/hHkDtjCYE+BpCNmLCQEP4Fm3f/RpU1jzDvegyuJXjba5Cdbsbu2/S6rqwtFdsdaLRuLn/68gOGngBUReWPzzdTWVHBFfeMxCfw3EyeW4pIWARB+NdQ3Ap5s9fgnxaDT3Roa4dzSkk6HcG33oL3oIHkXHSx5zH9gcMNScFH3rV555JlRAM5l03kUNtBtnv1JZZ/1xXvdeuojYkFoCohqfl5X58AZK1Mj86hTLusK/kV+dz/7Rw2LYsgqF0BUfEa5vYfhSRJ9CpYRllePRlqAiszvEhHi05fBBI4lRHYbJ7JtCkxWrbmuOigz+E6aT7LpV5YdHpCKyuZH5ZJpr+d2Dod5+td4PTskZhtl/GxgY9FS8O6jtz40hs05pZQMGYkgQEKmwZraeeMplq1MciUyAR/HxR7LXGXjGbtzjLeLiwjW+dih1OPSd9EBMXsLrgbs1cHnrjoh+bX63a7Ka0tpqQ6H02VSva6Iry967jwwUsPuU/SqplZZO7cw7hJQwiLP4cKFp4iImE5RurRDxEE4QxWtnE3jbkVRAxuj9c53LPyT9rQULQREbhKSqj88ENCHngAjbdnYmdCsJlFmeWHPdeSX0Ctjx8XPHvoPX58vL0ZdfP1cPP1LKisg205zKq3Ub09By0SsuRZNvzX78/YkFi+u2MSd0/9krkZ0WQ4fJges5kJ8V0Y1i6Mb/M8PTYvYeOP8/UYB3vqnmx/ZgbY/AFY2yYM2sAOIhmvH8ymPu2QJImOX3YEYGz7x3ix28T9rx94Dxj10QA0tQ6G5qvIskzJx58jqwqFQZ5ej7eGv8bIJVew3LGBJ8a80nz+oD5+1Lyzgb21BTww+SEKCzLIzRtDnfV3NJoDy/drNBqigmJwlNaycNoOzD4WLnzoIszegQccV19pZdnPO9m1I5NB5/cmuWvYYb8Hwn4iYTlGYlW8IJydytZl0lhUiX9aFEmX9GvtcE47bWAgyfPnUfPtd5S/+SYNCxYS/tRT+AwdQkKImRqLk5omBwHmgyd7KkWF1IUe/WbqUhT+l1MKQI3Lze8Vdc3PGR0K6zaUcFvuD2gkCZ0MXpLnBq7bU88zzmqGX5XM/d3j+OaPPaCXybUrDKzwYU6thSB/LyRfLcG2MhqeHMkcXxvTwwfzWdQluB3WgyZMj/eO4M9lX1BRVUBVfSnVTRVUO2rp7e7BjbUXs9V3KYVLCsHq2dixrHcqXvYswmLbYnabiNZFsHf1Dr76YxoAkfpgahz1xPpFIkkSMbHtiYltz5w5q1GUg2+hubs2s/jzXRjMdsY9eAFm75Dm52yNTtbMymLjmu0YjUbOv3Qg7fqJInHHSiQsx0BVlOZ9LwRBODuUrN6BtbQW//YxJPX49yUqfydpNAReczU+w4ZS8vTTFN5xBz6jzifxRk/5+OzKJrodImHRl5RgizjyDdXhVkhYuhU3YJIlcgZ1Ajy1XFwqpMz1FKtbV+HZS8eNhIpEqFSPRaejXhdM/yXbuVVjIDbJn+LSRuyhJvL9teS8tZFNMcWk+toJq3sAgC6NYMirY0t0Cptcadz821aWbC3lgnKFeV1lrlt9d3NsPhbwc2ipM7gYXd8WgI4BA2FODmavESjDOlAof0OM1RdZljGqeuJMsfgF+je34VRcBOv96dKt6wGvu0rNIkhvYfqCTqDxJyXxHqg2svXrBjQGJxc/NBazz/6elezNFcz+egUKCv2Gd6PL8Dh0BlF+/3iIhOUYuN1u5EOMPwqCcGZRVZWSlRnYKuoJ7BxPRO92rR3SGUUXGUnMxx9T//tsyl54Ac3yy7kmohebfrXQ5a7xB/VW+JWVUtmp82HbK7E56LJqBwAReh1PJkXQaLFQZbMT4++HTpYZP1DPL5KZDaMO3NSwobCc/A9W0FCo5X2TllfCJXxjvRgS40dYoIkpjQ3MDN7D1XujCNU+AzI4Rv1Ezu/3UmHzJb7KSd6mPFa4JALjw5jwk0KvTBW/JhWXTyzDv/wKfUAQP3/8NdWr/sDbVYwrwoqkL8XrilHUbixE2mShKMBFvJrCp2seoUpbh2yYwbac2XTsaMS77i5GXn9wyX5VVfmpRqKHbzjhZiNxSi5F69+metXtOHROrnh4LGbfgObjNy/IY8Fvq0lpk8SIazqKpcsnSNyFj4HidiFrRSYsCGcqRVEoXr4dR3UjwV2TiOx3+L1o/u0kScLvgjGY+/Wl/PXXufLHn2D3fH784QsSH3uY7mM8lWBtNhsBtdU0xsQcti3d30rIX+utIdplI21lNi6NlomSjTcH9wYVJOngWYD2uib8lGDc9SW8GJ6Eo20S787P5PtoCRo9RdR+CJ7FmDFPkTB1J1nhvUnqMRSvGYF00lSS9uNTBLdpQKNVqSr1o2KwD05LMGFrSnkufhAfvLkUU2MtfUtnAGCUdeRadhEjtcEUpSWkYxcyB+jYvfw1OpjT+L/ds5CQGGu4igrdFPz86+nWr/8BMa/NXktedR7eOm+yXCpjA2/khn43MO2Pz2haYaZatjD+nqF4+3mSFUVRWTZtF+tXb6FH304MuDQNSZTdP2EiYTkGist9yBnegiC0LkVRKF66BUetldCebfCODG7tkM4a2oAAIp9/nv81GVALGrlmz1y8/nMbFQs7EfTk+8x59n+kqSr+cYdPWIL1OoZXFzM/MJKXq21QbYN9vyv/rLfx9Ir1/K7zxaLRHXSub3w4DUo2crSRmKFdUVWVu3fY/p+9+46PolofP/6Z2b6bbDa9V1KAhNB7B+migooNsYv9XnvvvV31imLvoigKVqT33kKHhPTes5vdbJ/5/bF84+VnQwWjYd6+8kJ2Zs6cOUN2njlz5jlcf8jFh8k63kxzoXEX8OaSs3kLP40tOey58yOqWx8mQ7+ObnXvsu2MO1AZLThrttJkXUXWagk/IuviewaePxkMCKEDGdy8BSk4hlpzJalSDxqeyaNE72VD2C6wQL2mkDaHwAUpA0jpfTl1295GJU7BEp2Ms7kG66E1mFL7MXvNbHyir/0Yusd257Ovl2BfY6TB4OTiWycTGxoY8+P1+Pn+zR0UFhQz7syh5I7+5XZUHB/lKnwcJMl/TIZIhULRsQKByh7cLQ5iBnfDFB322xspfqKlpQVzrBl3qAapTyLh23bRuDiPltXD6Hr0beesPr1+tYy5E0fx0MtzqAuyENK9B6EqAUGt5i1TMG+4BKT/mVDS7/NRsTIP25ZyglrNaEQtgsrJwY8PIe+txwx4fTIPXNqXR7QqVux5nX3rHuZgWw7ba358pNRYZaZCthA3ZDjm4Dimfv0a1l5m3ljjw9IGX319J9eOuQ3UQQxWZQNbaLSWgxVW6ZqJCO1OL6Ev3+oDcx9VtDaRawzhnpFvs23bEgQBWlv3AFDzxd2kVnzJDyYjvqhAQPxs72epqK9l0/wjWBo0tER4uPHW8zBoDUAgc+2XczbR2NjAtMvHkpqrBNInghKwHAdZkhBVyiMhhaKjSZJE5ao8PHYn0YO6EhQd3tFV+kd78cUXEQCLbKe/tJbKwd1Je+gZym+7ERxu6s9OoB41sQ4XxU4XbX6J0WEhhGh+/D4MNhmZOOV0NnzxGd4aCw+cdw4alcgjR5cP/nwxot/HvmdKsTSFoQJCiQiMSUHGVGlGXVWPQyUgj0ggfkgcam2g/LG5gxmb+wPWoiL0Lx3B5Q5csmpikihKn8inq64LvMJ59ClL0Dfv0zWuPxv69eHt5U+zctQrAGgirsTtdtJk3kDmxP58k7eexjYRpxjIZlvkb+ICe2BgttN5EABTUDkrVnahC4HIbbUxEIw83/sF8jc0oD+ix4QM/bX8e8a57eN/mmscfDFnHV6fjwtuGkdUspJf5URRApbjIMvyTzIUKhSKv5a1tJr6bUeIG9kDY6Slo6vzj1ddXd3+/z3kwyCAP2cG2p7DCfpmK1tfOpepztUUvzmIK7If4UBQevv6QSqRVIOOs6IsXBofwbge3SmoHUXt+tXc/da73HPxhYQdvcBP37sbt+DF4h7Vvr1L9uBVqZFMeoRIA+YuFtKHxiHqVNRVHsZRUUdatxHt64ekpXHFS2k47R7mPPABLmMjfrWemabeJAWbWekoI8icQI/4AbSUHiA4sg0cIjn73mRfzlV0j/WxNVjGnD+ZXj17UyTn81zNmzzb5XomDJ1N/gPfos5qAqB37/PZvKUAj2cPQaoKUiqcADgFAZVfw7aPC4nxheBMl7jwokmEmS3t9awpsrJg7mpMJhMzbh6JOdxwMk7dKUsJWI6DLEtKwKJQdCB7TSNNe0pIP6dzzqrcEWJiYuiRkcjZBbeACFXqJJJ6joLDPxCdMZ6pd37FG0ve5epN/+b23W9wY/wD3DC8C7udLna3trHf7mSv3cmjRdUk6DXM7deP0lALu77/lsdffY2zpp7JujVb8YguRCmIFq2Io0sI8QOj+OjTVwFQewwY6oIJdoTQW51LY/MdaMz5AGj1n5OQeuyrxIYgLVjakPCABGcNuZes+CwuIND7turgi/irXka4A3QLoxj+0sc4bpvHvtIwzriuO0sO1vD0K++wpsvXhKskmho/wtYyFJPXgt17iKb1d6La/TnD25x4gi2IbYEemKZz3+X6CiuRK91Eei2kn5/GyAH9j6mby+Fl0ZvrCQ8PZfpNg9EZfzpuR/HnKAHLcZAlWRnDolB0oNqNB0k9a0hHV6NTEQSBs889H54I5DeJ85XBm6OOWefqo3+uSpyNL9/GS6W7uf2M7rw7JBtJklhY38KHlY1sbmjl7Nc3cfGwFFSDJiGvX8qKTz7AJ4vs9cVR7I1hgWjFdrCFwUUlZB29//MJTlp9Tlqtddh3bKBnr3wMXIHd+wkF+9/5ScAC4Jd9yHJgssTEiMBA1sLqJZQcvA6ABslEpMqBeqCEKIqMuGUCHz20jSWvBxLbCbLISEsw93d7hn0Vl9Cwbz06g0RIfjKhJU/gCA/FEZ+OpqUGdYvIXuckCj60YvWYiEJPwkT9T4IVgBUf78Xn8zJ19gAlWDlJlIDleMiykjhOoegg9qoGDNGWn+QIUZwAWhNkToT8H479PLIb2CrBHUiV/8wlZ3NerY1L5+3gmc/28tWBGj45pxdnR4dxdnQYL+SV8lJzNR9/E+gd0aizuSDRxfTRg1CtrcdT3kxGmAlziZOYFglraCh+lRODJgg/XlyylbDwcjxuA6PG38G6H+x4NV/zn29eZXHNdwhH/wNwxlrJbMkkoS2BJz9/gn5dW9G2fIv26D+P3NgJVNd9iSOugXXv9MO+wkP30u4c6jGAHrPHkFe6lAOtregSUgk7MpZyzxvkdr2Ctl2xtE2YS9CQ86H0Bzau+phq13gkn44w0U7/XgKZU8ejDf3puKn8bTUcOlDA6ReMIChUmcDwZFECluMQeCSkfFkqFB2h5WA5UQOzOroanZY85j6+qAonzFfLGNfywIej7oKUYex5eQZ+UU9voG+0mV03jeSa7/exfGM5/UtX8/BZOczMjqPV4QUgpYuFksIWfGotj8w+A4A+mUnt+/r07T00bmsgUu7L+Tf3JThMz7OPvYTebyEyshmZTFQqNdqIXPyO+SxufIUarchQ4bSj8xHJbJRXUG+oJ1gO5vS4r8EGtepUhmbeQNHhu6mu+7J9f56UZrRXwIEjLmZfdTOy14tt5xBqFy7kc9f1XHTmf9mcN4EKdQGh9MBau4Xdn3xAgz0KUeMlKOsHJp/+PIbomF9sP79XYtnnW8nqmk7mgF9eT/HnKQHLcQg8ElJ6WBSKjqALDaatqRltkLGjq9IpbXfFc1tD4JXh08VueBI/JWzVzZzW5iRW8uEyn9m+rlol8tbUXFb0iOeGz/K478NdNE1zU2l1IQuw4vLBPLqpkFDdzz8SmTQji/e31WPoasYcbmDTyl20+VsY0qc3Kn01QaazAQhP7k7FAUjUSAzRzOLhc+9sL2PkuyOJjY6lS30XamtTcB9w43FoMN6WyujRB2lrK6e07A2qqua1b1MUeZB7HptJSJmK3gcO079RxvXuIRxdNxEuT2Ofaysh6c34G0TMOhX9e8axp3YDOjn2F4MVj9eDWqWmIr8Zt8vD4KlZyljHk0wJWI6DpLzWrFB0GFNsOM1lFViS4ju6Kp3Swl2V7f/f6urLgN1jmNfrUb6Lbjj66VbU7w0jWEwiWepGtrMPXWLSeXFQOs8sP0zKlyWMFUT6o+fhh99HJ0iUumUmrbMQlZ3Ge+N7t1/IQ4J1OA1eovcvYv7r+ykoL8egCcEb/DkqGeyOOXyyZjnR0hEAxkdE0ycxlyOFSxFFNSBjF2y0trTQUF+P7VA6urpK3JFxvPbyB4ya0oOGxiXo5QJEQzBqTSBj7oQQHzv0EbTFh7IpPg3fgTyij5TzwfytaC2xCEziUFIrNw9PwZI5C0EU2bXgHARdy0/ay+5s46mvXuS7tgUIiJi8ZgbFjSYs7uyTeZoUKAHLcZFlCVFUBlEpFB1BHx2Cd1d+R1ej07pncjc0osD7m0qJVVcAIUzQn8aw3iOYs2khVr2dOmETzfJeehR1I7jOQN3uSuqAa9UaLEECV+LgPgy82mpClmVqhqcgh+kAeGZPOQ1tHk7ffhsjG1dxZ0hgv6urB3FQPRifDPu3h5PRzYLZ2EKU/xAyIPvVxDSZuePwyxQaytvrqxFlZiTswqMvovRQFOqMHFrVekTBz5ztizkQeoDBTX4u/U6ibcZpeJN2otU2YUwXOM04gK83bWVPt34EZw1Hi0yz6GC/IZaNKSOYHB7BIFGksqgAQXQhisHHtNWX677nhUPPY1M3MtZwOhH6CH6o+xJ3ZrPSu/IXUAKW46EMulUoOowy2PbkCtKpuXFsBu9vKsXjWISreQmmxbBr8SamZrYQMaiORlEg1JZGiGMQLp1ITO8IbJKMeKCZmQR6MY7UVnGFLhaVz8UbfhdVBAKWF5oC+U3GSN5j9rvSMoBKdxCCcIhIezKvbLqJtIQ9DIvfwpqKIawoG8kDGLjRuIWQxL24pDZAwBObh1fWcOS7KASgWR0Y5OrT6jgUcogYVyibwprZdLGKhz5aS3zmaNLv+RejYtKZ8+x/ifAH4xf8NIittMo6vnT35eapWRTb87nnYD1LLHHsO3wOWosdrfd8AArKSnhw6aPs1WwlTezGyyP/S6+0bAC2vb2G7l0y/4IzpVACluMgS5IyhkWh6FDK79/JFG7SEqaRSGsKI35Ib2JG9KO2thxv6RyMBj96SYUYmU+k1odJrUN9qJkIwKr+cVLDrpEyR2zgV+vJqNFgC5J4IC0WryQxKSmc3Tkf06+ggvCG/VToomnUWjD7qwmV4inzZaDdUMeR0jFU1EzmlkmZ5Ffs5xHJyYK2IeQWf4pWLMGjEViXGo7ok9r3ayrYTUTvqfwn8gUAavTN7cvW5ohctWQN5Zu28MXo0aiNcdSrWtuXF4XnIldBtdXPLLPIk62RXLjhUy7TeRCbL6XP5H/x6Of/4cvWj9EJem5OvIdLR53XHkR7JS+tnlaijdEn+QwpQAlYjksg061yl6dQdJyfzvarOHEEQWCExsFZyTfRWFJFwrhMBk8cz+KFr+NvySTGmIVV2k72k5OQZRmfw0v+U9uY53O1l2GP0ILtaHmASyNwUUY0KpVIi9fH7O2leGSZiuAs0g0qGp1+bKpYbKpYBgeVkT42k0/3VWNNDcEQpKFcCuRacSPTEvce5gszOePpVRh37mVk9HZkjQ/B6yc0ogdnnzWY/2wIBCyCLDOj2UOPb1SkTRxI1Pxb2XP3PfgMMTSrAvVtMSVw7oSRqGwCu6oOs235Gp7U3cEEQxLPJF/KXFccsn8Vj3+4jiZtDaP1k3ng9DsJN4ce027+o3XU/MzkjooTTwlYjoOSml+h6FhaiwlHbZMyyeFJlBaTDkVOwrQxOD4o4XCv/yKarWj93Wj17yNICDwCEQQBTZAWrcfPBFHNx3gA2FIWSvLRsqKb/fjUAvFr97C5RwbXl1bikWXezE6mweMjr3YLR5wJCH4rsiqEOb2Gc9buarw9QikEzq4tIyhkOymOAST7VfitXua/lkeJX8DTkEuSZhQ33RZG0ba9DD9vMob/xLIXaBx0GbqvP6Z8ZQRyipaut75Fc2MdH59mwaZZh8kVQnJrMosbI/j20wL8UiAQflkzB4BEdw2vHXqEEUnx2NQqooUI3hj0HoO6/jSBHYAkB3p6VILyUsZfQek2OA6BR0JKUykUHSUiJ5WmA6UdXY1OrYtGjRcZ87XxiKgQKUWt96HXReLSlWI29zpmfZVaIO3oPa9GhlD/jzd1mdVeLlod6G4ZtLeAHbY2RoYGMTUqlMsSInks9zQS5SJkVWAE7n8ObaDc5fmxcFGLIW4BYuJL7DIcwu2op6dlIdeEOwhFBAHSe2Ux/qpzMJi0yEcvZYZVX1K+MjCxYsrb8xFVal6edwsGSUuBqZhdEbtYlPI1iXESkiy399sdkAOhVn5YT1y3FvLeiLnESTBIxy8GKwD+oxl3lRvav4ZyFT4OSg+LQtGxtGYTfqfnt1dU/GE9Cq1oELC9vxcAtScQTDjUC0GUMOm6HLP+4Ywg8sVAD8OoyBDunnsaE6/JaV/eR9bw7xWtvLy9jXPKPLyd/WMCOY/fR50UDFLgnF6QkEmERk2YRkWwrwyAR9IeIFRj4J7k/3Jn1v2Upy0kp/e9PDf+BiZkXoPfd3QQr0qN8FAzbVftoaLwtMBnEjQ+Po/5H9yHzRdG77AQ9ly6h7FR14Ag4QpeRDetlhAERgcZyPDdgdU/hdyGbaz55BFSkgaRrQml3mv/1TYzaUyYNCYONx7+g62u+D2UgOU4yJKS6VahUHRuWn/g1WFRcuHXtGLU1BDmCmpfvmrDCporG9r/rmv24Dv6SGV8biyyLJPWMxKVJvBd2VLnZIDdz+BGP3cddHPxgsXUNjfTYHcwbdMSPEII8XIxOn8dfSMzCFGraPL6aVUngeThgaJH6B0xkjRdBAd8XvS6a2gUZwIQjI3CeclsX3IfrjYrANYKLcb0yxBm/ZegseeSv+cbljeVkWfeT0SPwdz/zf3cPuAsgqTuNHkrKXJ7eOesHrx73xjS7hnI3sEPUSpczKTKD2l9ahB6t5NW2ferbSYKIlkpWews2HniToTiFyljWI6DLCuPhBSKDqf0cp5c++7B26jBJxpQiwJBO/WEhkcgeoPYFpVBXWgwL705B5NoYNLY8aicPlqOPlTp0yOS/m/04oKViQiSgFo3mAGjphJf0Eyb1o/GA9cVhTNlQzEVJhHowlRjMdudBjySkfM2f0d3UxqFzkBV/rW4hO3RA/iYtwE4Oz6TccNv59PdLyE3yGQftBNu9eArnUNZ1dtURU8nbMOZ6AQDGbeNRhDHsPZGJz65knpdEw/sewSAb7/+Fp/oAzmWF0dn0ndQYPLEoGAdwyZnIk38L98tGsdpu+8hxNFEm+G35wUamjKUOQVzaHQ2Em746TxDihPnd12F586dS25uLmazGbPZzODBg1m8eHH78pqaGi6++GJiYmIwmUz06dOHL7744lfLTElJQRCEn/xcf/31f+yITgIlNb9C0fGU38CTR/b7aT5iwt5mwB0Tjj41BkEtYj9Ui3ZXE7027uPf//43faK745CcLFj2FaWu3TTiw9s1hKGHirhgZeDiP2nvEcZt/5D4gibsgkDU5d1ok5rp1ipz4+5DzLLuxVJ9H+PcTTzRrRvp6nrWtYXzTWPg8VBsow+zPYIh8ZcBEK8WuHvE2+yp201I42s0NvUg3BpYVxK1JJe1MWDnxzT1uxb9hGRUWjXrX3qXNlHk3uzruSp/BAMOhPJM5qOkt3ZB69cy0zKFCRMyftIOoihy+vQzKbpkMUZJxi7+9j39kLjALOKbqjedkHOh+GW/K2BJSEjgqaeeYseOHWzfvp0xY8Zw5plnsn//fgBmzZrF4cOH+frrr9m7dy/Tp09nxowZ7Nq16xfL3LZtG9XV1e0/y5YtA+Dcc8/9E4d1YgUmP1S+LhUKRefkraoCGT6b8i9enfYfYt9fhu+8h/HZAoNKXeo43ntkLdVlQZw56RwAisRa9rsLGWkt5ungUKqi45CB2u590CQPwxahxZ8L9tfyCREjaIlpYebt59JFV4PGW4pBa2BSbAbrRk3jwLBcLrVUo3XmEdEa2Gd42SoeiWvjma4P4hUM7N12DQftmYwZ/wZb0qYDcNDSi/0pl6L1yXy7/SyG/rCXGXe/RX5hAUnRsdj0HjxHSpmcfDYpeyLJaczhfuft3HPev361PbqnJWHMuId6lZp6a/WvrhtpjCTWEsu64nV/8iwofsvvClimTp3K5MmTycjIIDMzk8cff5ygoCA2b94MwMaNG7nxxhsZMGAAaWlp3HfffVgsFnbs2PGLZUZGRhITE9P+8+2339KlSxdGjhz5547sBFLysCgUHU/JxHLytG3dCoCxSxpF9Q5kSca6YQsANRMuonDAOBDA16xn/xefEYydxjoniVXf0nfjfKpfvoucZgkEkZQx16LvPYuE81ORD7rb92GpsVD9wGZGr+vJWU2jOX3wBe3LQnUmCte8Q0j985Trn+TLUVtIHPAeZhXk9j2b5YfW8vCG2/nvxqs596NtdC1bioSA0dpCbvF7VMboKbLEo5OcjKnbjtvZwOhbZ1NdVIgAlKxfhb5fKFo0NFqb8Hv9v9kmo+O7IQCfbH78N9cdmT2SPfl72N+w//c1vOJ3+cNXYb/fz6efforD4WDw4MEADBkyhPnz59PU1IQkSXz66ae4XC5GjRp1XGV6PB4++ugjLr/88t/s0XC73dhstmN+ThYl061CoejMGuf8B4CznrmBF16bzaHu3dGt+JTG0G5YuiXQJycYsy+QYr8vexls20ZSWxmyVkuPWx5gTMh4xsVfwoio6bjbHACIahEVespCVFTF/ZinxCgZmF17LgWHDxxTh65hXQHQuAuZ9MPq9s9XfnUJ760oI0jr4sxBIayuv4gQnx0RmTCpgr3dgtmSksRnt9/C9P51iFoTrrZanrjzJvIPHd2H30dUZiLTJkylwl3H0ncX/WabFNQfwiDp2VS/+TfXnZUzi/DwcB5d9ihuv/s311f8Mb87YNm7dy9BQUHodDquueYaFi5cSPfu3QH47LPP8Hq9hIeHo9PpmD17NgsXLiQ9Pf24yl60aBEtLS1ceumlv7nuk08+SUhISPtPYmLi7z2U4yb5fIgqZXyyQtGRZL/02ysp/pCkK3sgqo9t3+aQdA5nX8T2PZGs25GAvzWwfG/reMIOOhkaPJahlsnEf1VJnDGdGoudEH0UhsbAHEK1+S2YvTL2YA0DbhrCuulGGoVAWnwPPkJjo47Z36OzHmXdOesYWBODzi0wZm0DXYod3LdnOHk1MdwzMQKDz9i+fmOQjt2D9BwIyWHQgEUsKlpFc1M8TdeOJ+fOR1E57PiLA5NmysCCl24gvkcU2V0PI6bcS8GmeYFlXh+eHVuRpcDxef1e3lz8MndVziXRb+H2off+ZvtpRA0PjHsAq9XKnB1z/sAZUByP330VzsrKIi8vD6vVyoIFC7jkkktYs2YN3bt35/7776elpYXly5cTERHBokWLmDFjBuvWraNHjx6/Wfbbb7/NpEmTiIuL+8117777bm655Zb2v9tstpMatChjWBSKjuNzuRFVymPZk0XjqyLr/gGUjHmVSx6bz2M3nMnwjEiG/M86eUNGsyH3furlLFamPMSSHi9zZ+VlhHgiAMi9cRQCAkfeWE1QrRH94tpA2T3DkSSJHRs3khcNk0NSKC4qR95SwmXjLzumHjqNiiMJtXRx6hGAlHIn4ZKdKmDr5go+r/FQaHie86OKiEz9BFkUiNAWsGr3hSwv/TeeJLg9ZxwqUWTfoJF41i0je0g8BWuKsJVUs3nTMEIiRESVn4rWJwhbacC32oPXE4d536cU98vg4a2PcEQo5WztZO6e+Qhatfa42jAzNJPpg6fz5YYvGZsyll5Rvf78iVEc43d/A2i1WtLT0+nbty9PPvkkPXv25KWXXqKwsJA5c+bwzjvvMHbsWHr27MmDDz5Iv379eOWVV36z3NLSUpYvX86VV155XPXQ6XTtbyv9349CoeicKtfuJXZodkdXo3OS/FC8BmxVJISZqAqKo7jBccwqsizjdQVu2saO1XI4dSNF+gpmd3mUpSGbKDfVojUZ0Jj0dLt5ImFjAvfCaqGMlC3TefOr9whqaaT/iBEMnTWJElUdfv9Px5GsO/Qfcnb5GbXDRlW/x1kSMoBvxAd5S/MsNFdxjm43OfFh3OYfw6zVcwjutpES/USWNc/EI4o8PWIYqqMpKJLj3Gi9bgrWFJE2NJbel4zBJ/WmR4+FDOr6BZLaya7mj3gt0cydPesZypPM3H45kiTxbs/XePDCp447WPk/l/W4jOjoaB5d+jh2b9sfORuKX/Gnb1kkScLtdtPWFjg5//9U8CqVCkn67a7cd999l6ioKKZMmfJnq6RQKDoRn9uD5PaiNZs6uiqd1NHeY1cLapVIcriJovpjAxZ/RSHNYV0R/R5Sx+YyZPAAAEREXoj7kCVBa7BXFeH3epEa67CtrkerL8d+STKt2jCqdwey107vmY1PCiRj+/+vFQCJ9RFc/52E5YiA9bZXUH0rkUc31qtGYRR8SIIad/UBks2tSCYVF76zmx9Us9A1RDNiUCQJpsj2svr3G0lEdhPRF+o584bXGTrkFnoER1CYdyZb909nkzSMfwXfxNz0WFZGxbdv98y01+nbe8hP6nY8tjeWUqISsbY2c/Gq+TiVx5gn1O96JHT33XczadIkkpKSaG1tZd68eaxevZolS5bQtWtX0tPTmT17Ns899xzh4eEsWrSIZcuW8e2337aXMXbsWKZNm8YNN9zQ/pkkSbz77rtccsklqNXKWBGF4nhIkh97TSOeZgfIoFJrUGu1uGytyJKf0KwkNKbfTnz1d1f6/TaSxvft6Gp0XqIIqSNAbwEgNcJE0f/Xw+LeuQ6HMQaTsxZdmJk+qblQBBKBC/Iywyau/O8MWqgMFCloCLtiCFGJKfjTl/L1k4/h88Mnz9/J+ItmI7qdVKzZwJzig4GEgIKARqvjgnNuppI5lOZGkbynjvjKKpwE6rUxLYeKiGiaDMGBSiWCv9yBeW89FdlpvJ6Zc0ydk2N7YTxrBmENL/P1ijHEOouxB6mp0Cbwiedy8nQ9meLN5+YMC9GWZDYb7qLrqpupeX8saTftRa06/t6VAy2V3LbpRcrqliKozPTOuZCiumgu2bybtwfmEqxWJkc8EX5XdFBXV8esWbOorq4mJCSE3NxclixZwrhx4wD4/vvvueuuu5g6dSp2u5309HTef/99Jk+e3F5GYWEhDQ0Nx5S7fPlyysrKuPzyy0/AISkUnYuz2UbjwRJ8VtcxnwuCgC40GG2oCQTw+z04W20YzCEIokD1lv1I7qPd7rKM7JcIToshIju1A47ijylfvYuw7p0j8Ppbi+wKRWsASIs08d2eY3OPuA/k4dJnYDIFemMyElKwOM20GAJvZw7ZG4L2MhnPgsByZ8IrSMEvAqBSq7nv/ofIXzWfRat38v4TT6BvdSB4nNjKqxFkAUEGjU9gfdJ3aK6fSvIr3wBQGxXFakZRHxTCnsQfX94QvT5ERHK0bqr0wcwf0PVnD+vc3H+ztDCZmP3/RpBlLmE+PkFNnNDIJxFWRveYQUNTJUWLbmVq6bc4RS0Z1ho2zT+bwRd+84vN1exuY1dTGd1Corll0xz2Vi4EQcfgtCt5esDlhOlMbG2xc+uazcxcv5N3hvQmXKvcjP9Zv6sF33777V9dnpGR8ZuZbUtKSn7y2fjx45Hlv2+Whf+bQlyh+Ks0HSylJb8SUatGY9ITlpWMIcr8uwZ/W1J+Oni9fm8hhV+uJ3ZoNsbo0BNZ5RPK5/ZQsno7wZHhhGadvMH0iqMiMmH7O+D3kmIR8Dv2UFQWhFGrRavS0VpTiEs/kCDDj5v0PBJKdYhEui+aqAYf90tNGCc76Vm3nRTzQcq3TSBBzCG534toQtLIHH0e5wsyn8/9CBWQOmo806+9CYBDJQe49vmVbN/dwIuX3cmhL9cSVW2l+5yXGZCSyPbvX+crvw/f0bc1y8b2YeK6vcTanYybPBCz5pcvZeO7TENOnsLebZ/hc6kZsGsN6aWHqZlyBttKHyUz7zUyBBWbRz7FgJFXs/PLixm87zvy1j9Nr2F3HlOWJEk8u/87PtrzArKvAUQjyD66xZ/LfwZdQ6Lpx9+pAZYg5o4ZwvVrtjJz7XY+H9WfIKWn5U8R5L9zpPA72Gw2QkJCsFqtJ3wAbnHeDlJ7KV3SipNLkiSq1u3Ba3NiiA8jpk/WSdmPLMuUrdgBXkgc3+dv9faNJEmULd2Oz+4mrHsSYd2TO7pKp4bidfD+6XDdFm5efDXLaT5m8bNv+SjMDrw8kag5THxGAqs3vH7MOvPOvJLK2BQAyvuYKd1+MxXSXpAhrbYHYbpxHFj3A+vrZEZccS25I8eh1QVegd5bUMHUt3cDcD4qQlmFym/jtmfntpcvSxKxa/YA0FsjkLy/BP/gHN7MPXYW6V+zad9+Nj4aCEJu7RbITNukjUS4fiOhIVFH9+Nn3yu9SGmuwDprIQkpowBYWX2Yuzc9QVvrToKD+xBhjMYjCzw18CZ6hcX/7P4AChwuLvthDWOzu/Jw13/uv+d/fbqLWpuLT68efMLLPt7rt9JHpVB0MEmSqFyVh6/NTdSgrpgiT27PhyAIJJ/WD2ezleKvNmKMCyO6f9cTFrjIskxrWS1qnQ5DlOW4ki5KfomaDQdwNlmJG5aDISLkhNRFcZxickCtx7PsfpbTTLBP4IqIGQiVB3HZbFSHFRLcWorDFEdzs4ny/YGuFq9aQ4s5jJ3doqkNj24vThOSRvrYr0hqKeDQ52fgeD4fB/kUJUZiDtbTb/zpx+y+3PpjsjUNAk69ATDw+YInGDtmJmFhSQiiyIdJFh7ILyS1rJaDsUkszwk83gxkI//1f2cen4/v33oFMTyau16cy/6vHiF7/8uEeeqpnHMGwqQHsPSaiIBA2vmf43l9GKoPp/NVt+t4xOnD61+Czm8mt+lqBulGc9G4DMKCdb/ZtBkmPTP65DJ/+y7OjY8kJ9j4m9sofp7Sw3IclB4WxclSv+cItiO1xAzthik6rEPqYC2rpmlfKUigCTYQN6zH7w5ePC4n1VsPINm8IIAxNhSf24u32UHgLZTABSWidzqmmB+P017VSMOuI8iSRHi/NMyx0b+4D8VJlr+Us9bcSKFWS2yjzN0LIKbpx1ePPxsmcM52CdEl0GYxU5CWwdzRYzic3ueYYiKaGri8aB1XX3QhQXFZOCvWU3j2lQg2+CE3HRVwwa33E9atO5rgwADaLQV1nPf2NgByPc3cpwtjf+IaKhrVyLJISpyfsSPPw9Wo5Zua/5BhsyIn7McqxhIjFVOmG8VlQ38csrBj/34yU5IJNgW1f/biXbfgL86nz52PMLpPoM6yJFH5+QOE7Z2LUe1rX1cG3rCYmRNqAUAlQU71WLpwFmpZS3CVC79aIHN6GlNH/naviVeSOXPlZvQaDQtG9EX8B+b1UnpYFIpTmMfhxFHRSJfpQzu0HiFJsYQkxQJgr22kbOn2n6509L5GbdJhjAnHWduM1+46ukhCpVIT3ScTfdQvf9n4vT5qth6kfkcBCCAjowsPJnF8X1S/MgZB8RfJHM/jdVfw7ZvvccYWmepwDf77rkH1WOBR0JQ8AXFcV/xlNejKWum5cwcR/UdS6nJxV4qVGnslr9n7MHPJV0xau5zytz/Dn2ki+MxJeNIlxN2Bt278wEfPP8romPMJ0obi0rqwpJp5KDeINSu+JUuo5tPQdO6dMRu/vZWN723kUHkTb368kNiYw6QKQdhzs5CNA/G5KsFRTJJ7NR9te4RhiRewM7+a4lee4QedAdOoCcw6ZwYNjU3tWW/FL+fjSk5GHx6OIIrsaIWRkgrRL6PtOQ2X38Nj9Rv4JtjEGMmA05PCJv1BgoKbefjGUQAcqGnl0w/2UfZJIU/uqOWyy3sQYzH8XKsCoBEFHujXg1uWruHDygYuSYj8xXUVv0zpYTkOSg+L4mRw1DdjLagkbkjOb6/8N+FsbsVRVY8xNhxD6O8bBKz4ZzjYtRsA7555HXdkGKh/7vn2ZUFjxpD4aiCAcbdUc+HnqxANRj6feRYAyas2c6W6mLOvfgRBBl9uEKq9rQhy4N9J2MguBD30JiWfLCSkrgetmnr8kkCwz4Ik+6kIrmKF9wiIIiqVl/6u7nT3J+C0VFMaWoBTLCLcbGTYeT8mI11d/B3lVZ8Q595EU5GZ/DVdsDjd9CquoFWvJaLVicnjxabXUtIjiwpPGyIC1749H9xO9C+n4VUJlKSPJGjUg1z3w2VU4ueasNHsbraySt6FyaViRF4ks6+ZS1rvwNtKkiTx/vIi2r4M5Ji59tVRP5tb5n/dvOcIO4tKWDB5JJFazYk5YX+Rv0MPy99ntJ1CcaqR5H/cFMSG0GAistMwhoUowUonlfrVV/i1OqYs/5TQGTMQdD+O0/D8z1ueOkssGE3HXEQkGbZ7qmm5MAMZePuqZ1l4z11w5URi33yByBc+wxQbS3RoFrLkp8vVQ8h5fBphN2Rjj3BwyNOCWoIrLzuf5DA9+TEr+S7+QxwDQQrZhNZcTVNCNvtLd7Xvc1TqFDKcSQA0imNxR8TQr6iCMIeL5EYbJo8Xr0qFUdCRtb+K+CYbEjKvXDGDd/99PWtciawdGs46ywHGL70EG37eH/QE75duZK0/jwmunnw1/Xvi2mL5+j+P09ocmA9JFEXOHv7j46Cyht/ObHtf1xQQBB7ZX/yHzs2pTglYFIoOUr+jgOiBP58/QqHoKPqsTFqmXYjZ1YrNB6qwH8cc/W/wAuBDOGZcgVfQs89ay4KGQvakd+VTtYV9NU546weqr7qZI2PGAuApb0F2NaJNjAEgODGKllQTlaomxvcfQXR8KlHpn5KdvZrM7FW8sXcve8sHo444gsn9PDWF5/Ddkp6sWf8ENeW7sPk+R7LmcM3lz3HestWY21wYzplOwvffkbhsKcK0q1A7W9G1NZKZMJiJNzyKSpNIm7cV33gnAJ83BwbD2lQCd6x/iJZgDxO3RBO7qplPr78Svd+B31PPpw880X68K3f9mK+motT2m20brlVzdf+e7CgoYP3RwEdx/JSA5TgIoojf5+3oaig6IZWS2VnxN3Oodx/C57+L3u+lZshAfNXVCHo9BeHJfOaP5ptPl3Fg50GcbS4OW8LRHx2g3egKXIBPi+vJ9OvuIv6qIUzS2Zm25av2sv0tLdQ+9TS+OieC+sdEiDXFlazYv54odTh9Jo8i//C3aDQuBOFM3j8wG1VNNt7YFEaM2I8n+BE2FU1CkPz4PG+zv+AcJJ9A78HPU/TRB4i+wEBh54Iv8axahcfmQVj4Lm39JpG6cQu93nyC7OG98ZvHIIbNaq/DLcFtXBDqJkXnp0TrJRqJmMxudAmJQAXY/YE3mezNDj66fwMttW0k2X/sIt38cT41zW3sKCn92XmS/s8FseHERkfz3z2H//zJOsUo35bHQfL5EFVKUylOHFmWkf9pz4MUp4Swiy6k8a1jk4SGnjeDTw6r2BSTDXkeyCtCkI/gnJjId0YTA7/dCVjBFIqjqQZdyGn0Pf0ihqtEDl5eekxZTe+9R9AZr4L7UPtnC+Z/DkCdr5HHH3uSYSPfAyAmLBdDvZ88yci+ciuznQ60ugzWez6kcs9w7jx/Flu+uYGWQjP7Pr2DKdsPHrMv46hR7LniTnRaE9kvPMChnS00VR9kb/EWnj13BAC3fzCeM3INrEj8hlyLn6SgSIa1NfFeo4ofWMk9O0PQnX0hrvoGKp3DAbDWu/n4wc0AaPQqsqamsHvBIV5+8QM0Qg2rc/tw6/QzfrZ9RUHgoq5deGrdFkqdbpINv/1qtCJA6WE5DqIoKs/rFSeUrbyGoKjwjq6GQvETUbfdRrdDB7l65guUDRwLGg3BEyeiCo9gkLeWtVf04N1hIdyX4iWjrgWL20+Z10eZPghBamNX42dcvvUi+n0wgFtX3sr6ITOpjh4IgO/c64iZ9wmCqEYw5LDxoc9Z9cwnNLha2vffJao7Hndg4GVF8ZtMTVvCpH7V1NiDGfXcUv617ikqTZWsj1nP7Wv/Q6/p8xh/9RzMCSms7JFOS2QcqLTo+11F3VPrCJUFXJGp1NX72bDgCAc3OLDV//i79+ys2ZxrHMNXuyeh0zzGhaPW0WS4Gx8C/aOvpiGlP102HSFq/WrU0rE97TFxJi5/dii1ZXtpityChnpa9Uase3exr6LqF9t4QoQZnSiyoLrxBJ65zk95S+g4lOTtIEV5S0hxApX8sJWk0X0QdUrPneLv6aqXNtJ7v51hpa+jri9n8vgHAbhuVBe6xgbTIy6ENrebzKggzn96I1aPjy/uHIzVbuXhb59hq2YlAClNOUytHcfwRc9iG3UmzuGRJH3j5kiuBTnMApUtxNarKZELKdYM5YzJMXhaXZR7l+NwVJPapx+5/WdTWl/GVZ8/RLVpG5em3olRauXdonfxCB7O0p7HndNuRvBJlD61EbfeR0I3Pa1rq1GZEvC2lLNciMErgMlcwOqIHBb3NfFKMJQ1OXlpZVP7cRuDapFDvwPRwc5Lvmb/Y5uJkQQkyY8oqmh1luMe2Ie9m2uweSScxkrs5kKCNWHMvPQiNOFBPPHSy6iCgnjy2qt/8c2hm3bnc6Sqhu8mDv9H3BArbwkpFKco2etXghXF31qiSYcsqtkSNxOHNgK1FEis9urqQm76JI/Rz69hypzNfPLIRbzmm8VE91pCgoJIiolnP4FcPjPTZlFuOczSkA8BMK/+iuhH38Kd9yG9Zp3GhGsuJEbOR7P6BZLGZ6L2Gln9RRkb9u2lzVmOMUhLbv/ZADiFFqpN2zCJAreOmMm1o67lu3O+o3vrACLXDeSNO1eQ//QGTJIOk9NEdUkQIbdMQughU2mIxyPDoMkpDL75QlbkGhllg2l9cnl3vwvRqOb+syOIj66lzRGOs/xykLU0PrKFGEmg4YwUDqYGU6L2Ezy1KxE7F3LODamMnZxMjBCFXtIhedsIjzQTptfR57RxGOpr+HDj1l9s37MTY2lwtJHX6jzJZ7LzUAIWheIvVrVpH8Z45XGQ4u8tvmsYlWqJmD6p9Nv0HT4xEGDHqGx0M1jpaXYA0GaIIVKwMVo4yJ6VeVQVVODQ2OilHcCdw29n7oA3KY90c+0NEdxypYonZoi0Pn0zUQmZAMRecx0ADa+9iqn1CK2Ci9jsb9GYq/GG7mHr1jmUlKyjsqkIAIckc+6HZ5Nfnc+85zYy9MD5ePQOwvQqwvyBWb11MgQ3Omh5PQ+bMY7dTj+pMUZ6TkpmxIFCPBqBl0ZmcfOSg9hq2zhnaDJX9B/IihtmIuqqEdQtBOl+zJNiX72ZiK42ku3rsd86m9ZvP6DkjEnw/lNMmd2NjMgk2mQ39obAwOML+/bEEZ/M3rVraHQ4frZ9h4UGYdZq+KKy7iScvc5JucVTKP4Csixjr2igbtshQrsqk/op/v7SIkx8q/GRcKgZe0MjU0K24vAbCPb5OeSO4qAzMBv4gPEXUvnVNkJwsOSzJtyqCq7xvwTAXTveYXPGZvwaicbgVsLEOPIiaviXZwuRX+9jpOjBb0+mqvdwJufvozbse2RjMvXlPYnKKkPCRav9BVrtgTq9kACraxNZ6irnqTffoW/deADOvqsvCVEx5L+yg4PVh6jT+GmVG3AJbYQuGQZA1hnx7PvyCEQEyjp74yFqtwWChW+3VfDA8HTO+uAZJFdvenUtY9GlXyBJEjs2rENcKxDy9HzsZRswDpxAxA2XU3bR2cj711Pxxg4OmArpE5eNJS4Mq9PFu/sOsyE6maL03lRt3ce80QN/0r4qQaBPl1R2l5RCt5STeCY7DyVgUShOMEmSsBZUYiupRfZLRz+V0UYEkXrW0N/MhqlQ/B2kRZooUku8eJqJV3fupWHQNAAeL3iRl6ueoVKKwz3zC9Iyu9PwbRN+nZqJ5yVSdqCaA+sDj48S7SnsadpHfaQRWaunNnoGkrQHj1RPS2sFFd5amg5NheRcFiWfyWxVKSGiiyK7jcqd2WRFnI7f6EQw2FDpWlHrPdw+4Qb+rVXzzr1rABBFgdK1duTuTZinprL7ve8CByCARtBgDz5CUGs6i9/IR0Dg9Qgd4TPTeaGwhiPDotCtqKatxc3Ud9dxSe5pPHSkkbxDSbywdjk3jziN/sNHssP+Ad4P19Bw/lSGP/QMlUt+QAas/QaxVXcItaChsV8WZ/ywjl1qA16VmmSNFqPkZ7Woo8Xjw6L96eW2f7iFVQcLaPb6CFWmp/hNSgspFCeIrbqWxu1FIAgEJUcSNyoXjU7b0dVSKP6QeIuBNi18cfA6cu0FAGwx90DfbMOFinhVFW0fDKfepyVS30ZpWH+69MmgS58MDm1ciDZIwGUzc2XOtawMlVngbWNp9zScbdOQvdWcVeljTriVzAmJvPD1elYeMdBfDGO7WEQwBkL1ZiqaqrE3OPFKHlR+Pz6Nho1bX0PXFo3Zk0VoigpHrcCelRXsWVmBS18LFpg46ix0Oh1dc1NR6zVM/XYdqQfsZFR7GHH1GEKTLAzrGs38LzbwZG81DY06isvsPFbciiCALKvok5AAgLPNhuPx52hMDWLs/U/gd7upfvBBBHMQK/v14ru4dCotkbhtfsJRcZbKy2VZCfSJi2FFo42L9hTxclkt96fH/6SN+5g0dHMUsquuO2PiE//K0/uPpAQsCsWf5HO5KV2yHYPFTMqUQQji33/Ev0LxW+QGJw9qgpDcVwF3AJBlL8Ij6JEkFeDHqPa1z3J8cHc+7199OoLZQJh0Lc42NwKwd9suFozORJBkcqMDb4AsXrcYyEFEJi4qieevmsnCm2dhdfdgpnE4thQ73a+Z1F6XwvOvx5O3Elmtw28ws7bvQwBEt1YRnGiEpHgW7/kBWQzUxWDQ0/NoFumdVTXkmS3s7mpE62wkZnc158WZ8TiclO1dxwx8qEISSByUwbqD+SxtCUIduZpX1mzAUzUDzzf7SGryYnj5JVQqNXl33oGxxUbQM0+xpcFBUWQgEPk0JYwRybmIoogkBXpWx4QFIwJbrT+m7ff5fazZsILgvLlktO7kfm8onh01EP/IyTmRnYgSsByHTvHet+Kk8Ht8FC/aROq0IaiV3hRFJ+GpaKVuTh6jEPB7U9k4JJTee6xY3A4QHT/7ukZ5tyR0zlDcTTY8lCJKMaiB9NAdQCayKJC+aj2GyiZaamIQE5xcgAXW7mPcjmWM9MUzeoKZ5t0N6Iv0+Fxu1PpAUjV/RSGC3kzI6efjrakh1FNHszaK4ho97sZgaF5Fv8Hz8fs1uF1BVDUX0rAynLDQnsyxpaLzhzB2SzN1CDy5oYjXNpQwWN2ETuXipsuuISIlBr/XzWl7ZnO/3sbXqUP5ptnPsi8Xctn3dson9WR879FUbViP+vsfaOvbi+5nnMnWVXkALIgPoq5S5shrZxCjPchceTKL/AMRUlIQ9G72h+xlqcrK9nUb8OVtoadQxNiEg+xMnUZs9R50zUV/1an9R1MCFoXiT6hYtYvkqQOVYEXRqWjigwJBiQQqv4Hw/Xezr9c3GK0FIHvRt4G5cgxaUznOtm3sCo3hsmvmoVbrjynnqyVdcWjT+XeIDbRe3D47n6zzo2pzgwxSlB5kmSFHqqmwaOhyxrU06T8mbOOl+J8KwR08AMkYi7+hFEGrIXRMIvrBV5NsMLXv470rPkcdbEWvb8PjGYBaZUWr3QhAU/M3DKy9mkd2DwGM7dvIsswit5+N2mQiUgLzGZV9fi/J3grqp37ENX1PZ7bbQ8GkmfjZS9LKInwuNzdtOULm6Q9w6VmB3ps+9Tb0DRpcodFUf3SQKm6mKWIbktrFeNUR5rfEYFJ9i44V3Lobpu7NxJgzBEtMfzj8EAlpEwiPSaRk9wZ+nLFJ8UuUgOU4KB38il8iSzJak6Gjq6FQnFCCIBD/2DC+X3oE1Zp15DR1JyJPjyZGgzYtFs+RamxtcWyasId7DwUyuk5ZeDZtumASYvsQZYjC6a4nU+NFFxTBeT37oVIZcXvdvD9/CQCqRjeqpVWEuptQi2ZCHIG5hUL6DIGNoMKK312H2LwfANnj5cCtT+CMmUvq488SEh+PITSMMEMY4RYbQnMmA4c8gSEiDkSRysqdGI3hRH+yAIDGbJHW2Bjcm2qQqzbjaVpFrimSNYvMxOhayMp/k5LoiaT0PR2AT55cScGAq5iy8xNMZZt46d93M5rAsmUfNLHsg2+YggnwcXhPYEqAuNE6Gg4GjsOpMjFvYgLr8vrzFisCnw0z88SsW/F73DgffRzvvm9QDT0LadNX4GwBg+Wkn9t/MiVgUSj+BEEAv8+nTGKo6HQEUSAyKxz/+m8JkpPxevvSejgc+bAaSEQlNjG629mcduRLqj1WttiKaVCrSHU3Uee1kSDayIwCTes6Vq/pQfXm69hd0x3JqMKiFhiUGolD9mM/3IaKHmidocyZvRiVykmM6gEy4g6QfeebuJsb6fpIOL4jebz18hvUhsfA11+31zMkzEjXojMwFulo2VZBM2WUqR14h9nJHpxGSOUQACJim8ke1gf1aV345PovANA66tn+ybsAFJiz6DdxJgBrVi/lXpcPGT9L+pzNnXI1/502kzsWtrTvV1IbMUa4icgIpVgyIarA0ZyPIKvpOmQsBzctYdlLj6B22Eju1ZXSuEPssQcCm6r59xAtSGCrguicQIG1+yFl6Ek+q/9sSmr+46Ck5lf8kpodhzFEmAlJju3oqigUJ1yD3U3Ec1HUyRZGSK8hyhL9aaSfbOeIoGeJEMutwsdMFLYQTSNawc/90lV8Lo9FENroEnYQnazHqHEwaN9wytR+5gd52svXS5DuVTEdB5u9Dsx+P0GSQKSQ9JO6aAU7ldE70Xvt7LPFY/E7iA0Cr9HHIXcOGlMbCWoPCbLMf6xx/N98yV0QuQwdI1BzMPQg/7InEe11ckbxO+iNaay3xDPQvQujtYFWnx69WeSN8IuIFxqokGN5XjOHI6EDeLj3+Wi9Mj2rS5i4KeSYun2XAIUuNxewF7ffxJeqFC7yrkaQ/KjLixFEN2XRbVT5h3MoZAhr/FcRrW3lTPfjFKqT+Vx8gC/kEXwkTzyZp/NP8fgkBncJ5+MrB53wso/3+q3cFh6HThHRKU4KR1kDUT3TO7oaCsVJEREUGPQarFNx18iuxyzrffRn+vo8zM46CmOnEOSspEePs+mijzm6Vp/29b16K108EveFaHB4/JSW2mgQ/GS1yEhSPT10VQhGM6qQUIw1B1D5tLQ40xCEwAhflxAYJ+bSBNEztB6LOQydvgsl9XuYMLkXgqgCoKSwCb+1hokJEBrRws6yNu5risMEXCkkc8dpGdg+fBgZFSFTL2RCdDQwA8HrJHLLO7xanoBXUjFt7ACGbLmFbGkP42w7mLbpM3oN/pJtSamUmH2MsTdjsIaQuM/OlAqoT9eBvY24pJ7cnZ1J48ZCWh1NiMPPwZq3mWBzOpOGj2OGu56gzYFJFM8fnIk7PAPX+ljOCbWSkH1sG//d9Evp2JE2SsCiUPwBHqeL8qU7CMmKR1SrOro6CsXJM+Z+DCsf5dL9l0FEJoSlQVAU2OugcBU4y2Hyc3QZcBUAM36pnF942vHpk0+gDtmNWFlNc34Y4OPHl4AFEEyotWb8kgm9KhhUOhwWcNjtYN+NWTZw2fAfbxpu21ENwNIKGGJPJM2s5XBTIw7gpSY/0au/p234LqKadNwQVcCZgwe0J3N8tGAKtmYn1+bIDJZ9hLQ9TL24B5NuKSHxA5gTVMMN9hjqLWrC8/MY3T2H1j4Z5H9cRmLL12So99O19lPafD2QswYyf4cTs6Oce998GUmSEB8JDVRSBTVCMmcN7oohMonmilR8DcVcOjT1j5+nU4ASsCgUx0ly+2naXUJrXR2CSkXKxAGo/me+EYWiUxp2CxjDoWIbNB4JBCmO+sAA0eShMPW/kPuLYcqvkmUZc0w5moRd6MMiufTRL7HWNlNfWk1jVS0ttXW0NjTgaGnC2dqE2FKK32tDXePHZw7FFZdKqGziyB1L8Km8SDqJG1wWcmQ9X3m8HG60U98io5LhwsMrmF6wnIemJVEENFq8PFD4DHP3vcZlWbM4s+cFnF4ochnB2PfJGPDiB/xiPE3OuzFLZXQJiwQ7DG88xLnvvgMEMv1rEpIYN2xz4KD84KprRl+3lDOFLnzhOAtns43Xv9/MSCmd3uIR9iZcSJezH8AQGniUHJLQlaLDW4iU/CAqN0C/RAlYFIpf0VbVRP3uImTJD2oI7hZPSv9B/4jp4BWKE0IUod9lgZ//I8uBEed/UlPzBnz+NnQqP+HhgxBFkdDYcEJjw4Gcn91GlmVaG1qoKamkfH8hIW0CTpcLf6sX0QU+Cbp4VJzmCtTPjYwkwPvTlrHcqcZuKCXSGsR316xm8eZPeOvAOzxRNodBb9uxiGoO9O5HSIOfiswQhp7bDb1eTcMzC7EdTkDsbQdC6GrWYDUFEeIITHLk6NYd2NxeRx1uAEzkMNHTmw+e2syLgpdP/DfzeuTH9KqYR967NfT89xdYG2tx2z3Ikge5qQghIuNPt2tnpQQsx0G5NJ06/D4fdVsP4WoOfBFpwo3En5aLWqPkWVEo2p2ggL2pfi0IgeGx6d1nHeeuBcyRoZgjQ8ns/9Ogpm56ApYgFUFhk6jzplPvjqPKEEg9YDcEMuFqzGo+PvwhU/tOZfqIS/nyoctxbX8LgOSCBMJmXgY5IvXLviG0b09MvYNwrxIJ9behlky8qenC3sfuZ+buAlLmz2PKjRfBvHdwJlyAPiECYfPL+OQw4i65B02Vn4e/LQfgvNwIel28mOqHutDLthLvwxFYjh5/s5xGaZOLlIg/16admRKwHAdl0G3n5mhppm5rPnhlBFEkolcasUOUbw2F4mRrLq9DDKrFa9cTGd/zT5cnSxLh3e3IfojQfQKAz62iyKtjvz2OklAdTd5WqoQWXtr5Ei/tfAmtSsskl5ZuR8uQmitoePlRxHejMY64E+umav4v6dyRpn/xseyjqCmNHstLMGwVaROC8CyZi1oC7Vn346lrQ7tpDmqhCf8HkwkLGUQlM7kqKYJbLg7M2lyecz0lTcUI5nh0obGUe828urGB/4ak/Ok26MyUgEVxSqstOoLX7SImKR1D1/COro5CcUqpKm9CG18JrVEnpDxXdQEGtUzVwAeJHnA2ng0LkPLXEOtex79s9bwcn0aTFSLVIvW+wHw/Xr+Xr7p5GDHrKRKn30VDmJoIrRF/YyPmq2NwWa04i2vwyy3IKi9+WSCDIqznyVjP8yO4mimx/kCIVo/FsRtT1nikGw/j27UaYescfC3LaeIiQjQ/jk0ZcM4tx9TbWdiAbeNSdGplJvdfowQsilOSvbmJ2qICTJYwErrl4Mpv7ugqKRSnFKu7la+ls/lecwvXGb/jRGQgcRZvxwBoE3JRRSdjmH4rds9sVE8m0MdtZVTREXJ7jWXWwMc4c+EUrH4Z+Wgf+jf7X+E6QMpORt5wBN3ssYR07U0IwEBoayunZPOz6DSZWMUmdNQDIOuh1a+mNlKHXHgjRYv7obJHkxEdywr/RD50ByaOdJn8tLa5CTbq2HWkgndX7UcAwkxamj2BQEWrBCy/SglYFKeU1qYGaosKCbKEktZngDJ4VqHoIAUuER+Bt+x0phOTjMy47UUATKm92j8zqA180+ssso6s4hJbC0XxEwg3JbL2wjzy6zfxTcGn7Gs4QENlLQ5jDI11AykYcCmm1ibKv1hAUtdUEtKz2bvzPgBcvsPoQsHn0qDSehFEcJjU+G3RpMVOZF1NoOemxt4KaLlYv4M9vljm7IFX9iwjzuCn0hm49BoFH07Zi4xAoiihE6QT0g6dlRKwKE4ptUWFpPcb2NHVUChOaR5J4sV1e3AeTQvwgj+c1Qt/IFqUMXu9jDncSKI9Am2EhKATORgajCk3nnHdu6BR/XIvhDMkE701H3+bFSyBcWgqUcVZZ75H9atR0ApR5r40Fe6gpWYHbvsehvgPM0DXijYlgR0jL8HnDGyn8bo5sCKY/cus+D1zQKgiNCOShO5ZxCVPIKvnhXg9bVQVr+NI5XWozLV8ud6GWw4h1OKm/8hZBDkr+G7ZevR46R7sZmCKhZ1lLVQ61aQZPax8YBqyLLN+0xaWLtmO2ag7+Y3/D6YELIpThtftQq3M+aNQdLhVTa1oa5rYmpEAUuCRzC5LTPtyj76YGG8pYxt7ECuFcmO2BRocGJZtIdneTLQgE6nTEGsyEBdkIiHETJvdznLNWP4jLCbojT4UmVKpie6NkDSIPkNmofeF4VPVsOXApMBbTrKAzpeISc5Cq42kpbURnzOCkHAXZ90xkKCQMbQ2NfHBPXkEhYNaH0JMfF9Gn/FUez01WiPJWRNobbmTWsfTvFo/OrCgFviskF7qSnqpoVgK59/DunDeyMDAYofTzf/NiiMIArbmRkJDgpXvp9+gtI7ilOB1uziybTNdh4zo6KooFKe8K/MKGaESsEkyA0NMdA/Ss6HZTn5bIH/J2f2GsGHVd8ScnsWOkDCoq+Nyvx+b384RjYZCQcUuQYPdb0Syi2APpCEwRnZjkGMiF9V8R314N+Jrd5Jc9CU79GZym0WcluF0i7gStc5CaHIfNIbg9jote3MfUIe1UY8xOJCRdv+awwCMvugsUnvd9ovH063fpVR9U/GTz8O1EmGh4cydPIpeXX6cb8xkOLYnpbq6msjIyD/WmKcQJWBRdHruNgdFu7bTdcgIBFEZ1KZQdLSsCislWh2jbZDjcTC4voq7B/XmjI27sUsy0ZpA3pTCw0dYmhl44fgdlYpsMZLlZ/RsH3vm8XioamikvLkJQatnYFoPZOldSqoOMTC5J+s/uILkohJ6Lb4TlWBFzriN4J5n/mydTrsym+K8evSi0J6q/8iOKgRUJOem/erxqFRaSg7puMixhOaYbJzGaPpmJjB7wkQ0vzF1h9frpbq6mlGjRv2eJjwlKQGLolNztDRTdfhgIFhRBtgqFB1OlmVSjtSzwmegUuWmz84FxBZvolSlxnPXY/SLjyKuSxJshL1lh3hj1hmsz6/j9uJq9hsEMlfk0cUv8lh8NP1yYkiIiabM42PD3n18vWw5+voajMF2xuvuoFfjTgBUghWnZQraAVN+sV5en8QLk8z4gS+/2U1/kw6L201YtLo9gPk1VocDTVgoUd5qsFbTtGMPrxdvJjMzkwEDBmCxWH52u+LiYvx+P127/r0nPvw7UAIWRadWfSSfjIFDOroaCoXiqLpWN5IkMXdmfyZkR7Ot94MAeNRq3n78Lrb27E3E/HmMTBvA+qLtqFQiA+NC+bjRx8Zd1TS0NLAlQcU1bbWM/eodDF5Pe9lqvR5RlulhK6APm1lr0JPtFinQatCMnk3fiOhfrNf6w7U0m1SMsouU4Kep5nPuNT0HQO3Dj2A19sWReSmZI/thsgQfs63k9eKUJFAJ9I5VIZvjqWp20dDQwMaNG9m4cSM5OTmcc845P9nvwYMHCQ4OJiJCSVb5W5SA5Tgo9+X/TD6PB432OEfdy0o+Y4Xir3C4phWAbrGBi36wKzD+pMUUjtFdyYDdu1h279PsdsYS6unFK9esPGZ7PTqm1UocjNuH+D/BCoDW5QJAlZEDFy3i4FcXc31LHol1Mle9/w5dL4jA1D+7ff3WNTvwt9rRZSTzXbmdaEFm3pQcRFFk195WyA8ELCKQ6VjEdyu7seF7PyqVjZBImfjMMLIGpOGr3IKuppyYRBP7qiMx1BzilgefAaCgoICPP/6Y/Px8mpubCQ0Nbd+/JEkcPHiQ3NxcpQf4OCgBi6LTqjx8gLgspZtVofg7OVRjQy2KJIYaQZZxnHMRzdX1NDS5MbU5CHG1YF6yAv3AW7CYRaxHczpqZRcRWhsmXzBxYjPZrVls0hzCPDYGo86IUW/EXrOd/pvfo63Hw6w5/CVzWvIAuO47P11qtlL2/Tmkr1mP7ft11L/4OLLb3l6vlY++yCifBlEUsbY2Im97FYCN3S8nti2e8OLHyZw+BnV+CzVFEvVlVTSUN7J3rRuP62sIDebMi2fz3kcfE/8/HTBJSUkYjUba2tp46aWXMJlMjBw5kj59+lBbW4vL5aJ79+5/VfP/oykBi6LT8nncaHT641tZubtRKP4Sr36/j0xB4KXFnxMnxdAcO4nmVitmDTh1PUnwHCD2gjO4dvoYRFHkzcsXEuc4yOmf3YvkclP54GZ0STIlTS5SwqKYMPKC9rJXvPMm92XfgK/Mz1ZsOCNvR/C7EPzvUBAlovf5qD99HHqvH53PR8jgKYScPpHGulqqI6Lp52gEYP/u7xhSthiA8F7n4n37CWS9SNCae4jxmamT++Fr2wiAoIrCkKDDZoxh38bFtMhBtNhgmtuJWmdAp9Nxxx13UFFRwVtvvYXD4eD7779n8eLFaLVa1Go1iYmJf/2J+AdSAhZFp2Stq8Ec+cvPqxUKRcfIFl3sloyUrlIxy+4DrEgRGmLHxTBp3HCay2rQGnSoVIG3a+IjfFQL3XE32qh7YgWCJgIEkWhHKNbsYx/lvh85hq267gyS6xmGkbqCWvDLHIr7+fEhutYDZO8QWKS3QNdsNgQ7iS7bRP9NTwJw+ILvSEnuRdmwmyjcl0Ckew25wjZWlzgR1WEYaaBF68RmzAIgIjoedWEBKnyoNMc+jt6zZw8AI0eOxGQysXv3biorKwkJCWk/VsWvUwIWRadUX1aqZLRVKP5mXK4qzktbzLOTT8cl9mPxQ0XE9anl+qsvoCjvMB/ffj/W2n0ER2Rz9StPAxCXpKWk1Yxt26FAsOIvx5maiqrMhyX12JuSrcYkLGIj740+O/DBBHhr6XKsG0EWBJDlY8YkulUiOwsPkj808PbQV/44FhWK1DiqALB9fAvdPPcTJ7aQYuhNjC+c0+X1zH7nSw7l7cLgquWz79e2l/fpxmJATRejoz2FQm1tLcuWLePIkSMEBwczenQguVzPnj156qmnGDx48Elo6c5JCVgUnZJyx6JQ/P1UlH6NSi0TFTUBtToYQ+hWqnZG88rse3C17EFUWwAQ/uctYltlC2pJB2VOwEz0HVPYvWUH4QKkpOe0r2d11mMjlP6G+mP2+b3dy5arHuaRcB2JwSYiJD+r7v/3MeuctuE7Ju9eznVvfsaG2oPEyquId9cRXNiEVCEyKdFDuRUWOIZQ49ax4Z7b8FqOJnoLCiE9OpJJ44ZwcNP3tDqcjDn/LjZu3MimTZtobQ0MMg4LC2PWrFnt+ywqKkKWZTIzM09Y+3Z2SsCi6HSc9la0BmNHV0OhUPwPWZYp3L6fhNxI1OrAqNT0gSoObVhOa9keQhNSOf+BJ5l79fnY6vbz0sWXMvG6W7G1golWnPvUCFonmsgQ2spbaDO40TfUsnLf9/gd+xBEPZI4lyHmY3Om7DdZ8KtU3NvigxYrAMEzb+fKxXswOAUSumko21eOJcGISlQxIjaHa2q/YnMr5HsshEZ4uPfaK7C7Xfzw4ApsghdvsOWYfTSGuglP703P6HSWLVvGMy+/gd/vR6VS0bVrV8aPH09YWNgx2xw8eBCz2fyTzxW/TAlYFJ1OxYG9pPdXulkVir+T1ta9uJ02EpKvaP9s+JnTObD8XSzJKi596iVEUWTYhf8if/M26oo2Ul9WRY0vCo+oZ7PgJlljw1RahySuxtp9H0HFpUQA1WI0pZqB4INJCb2P2a9LbyRdp+X9jBhKrDY+Ka7k26AQ/PpMTAkw+doBrD3rTny+OuYsew+TM4iI78M4P7KWB71mmtFww4sbOdQceF0pJDyU8VNGk9UliU2HN7H92+00H7Lx0EMPte/TZDIxdOhQBg0a9LNJ56xWK/v27WPYsGEnpa07KyVgUXQq9aXFhMUlKjkNFIq/mdKCr9EaVISG/pjIcceaJ4gfUQSywNKFY9GowtHqYjCnuHA42wiJ1+FVuUGCereOQ8G7WfzuPgYMXEWQro0Gv4Hs7OcZGzeBe3ctIrillaSg3PbyrV4fbkmme5CeLuGhdAkPRSUILDlSS0ibBlcZrJm3iaTKdVAJP6RUkG7vjQporY8CSyCvy7c1gWDFJEHf8p7seq2ZPT1306vVQndfPAfUlajUKrK7Z9OvXz+SkpJ+tS1WrlyJRqNhyBAlqeXvoQQsik7D43Jia6ijS19lsK1C8XciSR7K9paTPigdUQxcdgq+vA2HbRFikBaNkIokWPFQgF/YQ1CGn4wMqPNcQeZ0gSPfPIffbWbm1HE0rbyDkLoGPPpwBuTcgkYwI3ls7HKoSVM3HdOj8U5JHQDfba9k/I5aosx6EiwG7gmKQCIwtsT03lvt6587qDd9d11JZVsffL0up1+dHWujn3qbHpsrHAk1wtFhu/2PpBKtEYkUzMScn8WInOObWLW+vp7du3czfvx49PrjTLugAH5nwDJ37lzmzp1LSUkJANnZ2TzwwANMmjQJgJqaGm6//XaWLVtGa2srWVlZ3HvvvZx99tm/Wm5lZSV33nknixcvpq2tjfT0dN5991369ev3x45KcUoq3rWDzD+Qhl9WstwqFCdVY+Na/D4X8QlnI0kSRx6Zhf/THZiz1Qyatxad7tjXju22OiqKd1LZeD1etxlLqoGwWBOWojdJc2+HYoA2OHhz+zY7R64BIHXpQoyCn76qAyR7qzhTE0GrW43VFkRBaTjr26ICG4SAFnhJshMO2AzwtmcbQ+Q2MgzrOVhnRexzJROGX07l2gV89e5n+MUB6HSpRER60YwKhyVevEPMjMg5/mvV8uXLMZlM9O/f/8816inodwUsCQkJPPXUU2RkZCDLMu+//z5nnnkmu3btIjs7m1mzZtHS0sLXX39NREQE8+bNY8aMGWzfvp3evXv/bJnNzc0MHTqU0aNHs3jxYiIjIykoKDgmfbFC8VsqDu4jLqvrH5uNWYlXFIqTqnjfUoLDjZhMGRx6fAZ8uh8A3WEo6jkcf5wGsVssxj59SLniSXw1hzmS/wLaEDX9BswjckogY3X9gs8BaJm5jKDYBDyN+/E1HsBbf5BzapawLSQZS0gYLT4/A71r6KopwSYFY85oba+LKvodRHMuh5vslLQ4aV2vZv5wkS+GieD4gjXnfo6ldDu9tzzNnq+e4bN5CyhvCmzrCd9JU1Ql7yT+gLnAxJjI/vQOG0nG0QG2v6WyspLDhw9zxhlnoNFoTnArd36C/CdvL8PCwnj22We54oorCAoKYu7cuVx88cXty8PDw3n66ae58sorf3b7u+66iw0bNrBu3bo/Uw1sNhshISFYrVbMZvOfKuv/V5y3g9RefU9omYoTp6mqAmdrK/FZ3f7Q9rIk4y5sQZ+hBMkKxYnm9bbww/u3kDO0D64Fq+DjA+guHY1p8FAafvgEYWERwtG7Bskoo39oOiX6+aAGW1k/KrdegaD1sd8gUx9sJV77JoONbaQOvoqY8K5ERWZTVbqGtE8vIX/6K2TmzgRg4bJM3MY+nD/0U5weJ0u2vUew+zkSs74hM/7HVPgbew9k9r/bAJAFHQ0Jb5JQ6USft49pFV9jNkJmv75sX7uDgbOuZr+xmjllc0h3pVCpqcGpcmH2melt6s207GmMyRnzi2Po3nnnHWw2GzfddNNxzQB9qjje6/cfHsPi9/v5/PPPcTgc7YlvhgwZwvz585kyZQoWi4XPPvsMl8vFqFGjfrGcr7/+mgkTJnDuueeyZs0a4uPjue6667jqqqt+df9utxu3293+d5vN9kcPRfEPVlt0BL/P+4eDFUDpYVEoTqKDB57BWZ3C5gfBFnwJhr5NmEo1mBoECu23wCjQOxswuBpJjPoAT9B8AGrXXoRoSyI2V4u9WWZ1sw+v6gCHIhtYAbDnpfZ9BEkSwyPDeajLBADsrjryVX0RfUaKrOWkhSTS6rWzr1XDLT9ch0owYhLDCBYtjOzRCgR6R1LqNLhbrTSUO+jqCvTKnPOfeaz57B0SjC2kZGWwu6IcgKenPk9yZDLf7/+ebwu+ZbNjM2t2riFmVwwPDHmA4enDj2mHwsJCysrKmDFjhhKs/EG/O2DZu3cvgwcPxuVyERQUxMKFC9snbvrss88477zzCA8PR61WYzQaWbhwIenp6b9YXlFREXPnzuWWW27hnnvuYdu2bdx0001otVouueSSX9zuySef5OGHH/691Vd0IhUH9qELCiI67Zf/fR0fWZmSW6E4SXYvSMDZmIQ3zIhWdhIeLuJwydQ2axBVXqJU9agsairdWfTKvYe0bl2xbvyB4tpkeueo6XvNKFpsLh58YgXBMV8BsGjKIlT2CmoaD1FrLea+8u9YYzRiNAWSuW2oPcQLwp0gwfM7G7koeDubqxZi82pA3Qi+QMBQ5dvAR2NVnFeRSl2lm526Cfi1dm7uGktbyV4crRZCQ83ElX/FgOS9uD8awcdJMaCC5Ih4dBod03pNY1qvaXj8Hj7b/BlvHXqL6zZcx4CdA3h03KPEhcbhdDrbh0p06/Ynbq5Ocb87YMnKyiIvLw+r1cqCBQu45JJLWLNmDd27d+f++++npaWF5cuXExERwaJFi5gxYwbr1q2jR48eP1ueJEn069ePJ554AoDevXuzb98+XnvttV8NWO6++25uueWW9r/bbDZlAqlThNftonjXdqLTMgiJOgHzBcmgRCwKxYnXUteGzx5FdA8DFbvBIxioGN2f8DADYToVJrefNGM04uefEq9poFv55wivgx64Mhqoh+qFz1EQF+g5kXwmRLWDM767iITI4cSaYnDKQSBDSOOPySIPugKXthsjalna5GVZqxnZ++M4lomJYzktbgANh3bwhONj5icUQwL46op4MrUf553Tl+fPexC1OjAfUKK2BYffRF3aWbQSGL6wftscxg69s71MrUrLzKEzOaffOTy37DkW1i9k6qKpnBt3LhEVEbS1tTF79mwl5cKf8KfHsJx22ml06dKFO+64g/T0dPbt20d2dvYxy9PT03nttdd+dvvk5GTGjRvHW2/9+GrZ3Llzeeyxx6isrDzueihjWE4N1UcO02ZtIbV3P0TxxKTfl30S7lIb+i6WE1KeQqEI+ODe9fjbarBN6Yl6QTltWgGtT0YtBZYHifVcEnX1T7ZzSNHUiLl0YRkA80Ke457aOKRQMGi+RdQ2QlArKpUVkDF7HAxu0JMz/T98VtPAPpcerzqGkhHZ6FWBwa0ev4fZK+exver5X6yv/cjt6InCYlBzW+FyAAbOuoCQZRNoiRxM4r8WsnXXXK7Y8ypnhKfSJ3EI47OuJFj/08kVy+rLuH/Z/ex27yanOYdHznqEtLS0P9mindNJH8PyfyRJwu1209YWGLT0/z+bU6lUSJL0i9sPHTqUw4cPH/NZfn4+ycnJf7ZqJ47y2muH8nk8VOUfxOt2EZXahdj0rBO7A+X0KhQnhb3Rhd4g0LqullDA6JFpNgnMvLM/Lq8fa97bsA28qNDgb9/OJNa2BysA7zf4ALjQHIUheDbv7qtkwKAQ3p7Sj5UbziFIqoNUB6+Xb2WXMKb9ypa94SAWtYpIrYYEvYYlqp6ER85lyeA0ShpKWLFhFdU1lexoy6bWkwCo8akk1HYvAyMDEyKqFh8hWO8kuHkljufjiHW6yImKYElTMV83FvP6gU94bezLpEUdm4clISKB9KR06nbXMWrwKCVYOQF+V8By9913M2nSJJKSkmhtbWXevHmsXr2aJUuW0LVrV9LT05k9ezbPPfcc4eHhLFq0iGXLlvHtt9+2lzF27FimTZvGDTfcAMDNN9/MkCFDeOKJJ5gxYwZbt27ljTfe4I033jixR/pnKF14fxlZlrHV19JcVdmeH0Wl0RCbnoXmpCVZkpVTrFCcBF2v6Eb+JxsJrfW0fxbiriXl1XgqDXEkugPvC8sIrGEg6tTh5IyejrO2kKK8x4jUleP3GTC31ENdEt9UFuPwmQDYV/MYAz+144t/DAkRCy240ZHZUE1uczUtJjf7IlNo0kZS4/aSZ5NBEAh2tBIXGkdcaByb5u8i1qnl7KZM1scKhCaYeX1mH3asKIE11XB5FkEbvoLSQN090amEWGt5QG3hiqQHqHF5CWl8mCuWXc/rp80hM3okAJIs8cj6R9iyZwtXjbuK6ZnT/9J276x+V8BSV1fHrFmzqK6uJiQkhNzcXJYsWcK4ceMA+P7777nrrruYOnUqdrud9PR03n//fSZPntxeRmFhIQ0NDe1/79+/PwsXLuTuu+/mkUceITU1lRdffJGLLrroBB2i4u/I63JRU5iPz+MBQWgfQSIDIVHRJOX2OmGPfH6LrIxhUShOijH94/lqgwVZ9nHH+YPJL7MSs/h+9rZEo/aI1KQOI9ZVR/DYB1n12XrOi0smJCmbkKRsdtS/SIswkAnjF/DUoQ3sLb8VnbqZ28vNyH4DF/e+mVfqPPgwcm5QGQvsqUiCiqjGPFJXfQlAkiaULZlGhkuxyECbVodK7eHZ+fsIs4TR6qvH4EnAJKt476bBXPnDQ5yzYB7Di3KxCGl0S49ASHoY22PNtNGPhW1deLj70cRzMqCDOwY+xotb7+fKZTfw2tiXyIgezuPrH2fL3i1cPf5qpmVM67D272z+9BiWvwtlDMvfX1NVJS01VQiCgFqnI6ZLBhpdx6emljx+vFV2dCkhHV0VhaLT+WZ3Fd/MX8Pt/zqdI3m72PrRawR5bJg0Pma/9y1f/Hsa1S4tjQk9SAzWk9OrL462NmTTLcjSZE477WUAPlw1BpWvgf7dvsYv+Xhvby2G1V4azSrSUi30zdZxbksbd7/5BHpvG4NmTaXnjjsA2KJKYIN/Ig0ROvxtflRuFVq/FoDglq54JDWf9HoRWRWYzfnVstdwqGHkLQPRqEUad63FcaicB1RdWR6j4flYFzvtlXzamkzeoDQ8niYu+34Gdr+XVE03GptsXDvuWs5MP7NjGv0f5i8bw3IqUO69/7jGinKsdTUAWGLiSOvzN0xH3TlidoXib2l8djSLNWqevvcJMlv3I1kS6TNmIDt/WMan102lyqpCo/MS5HNQbpMpX7cBnc7OgIEgiN/zww/1aLQxxFHKdqeGN1Y8TJguivgDMSS29kQwqtGsr+cNpwYx1Yjf10ZiXCI/7FhLz6N1yKCG3uLblJsM7MyMwK2JwG6Pom5XBvuiV+O0xJGo74vTZ2fetOfotf3oM6CN+9BIMv1doajDQmmUJUJ8Mnn2Sj5u7cLVljIiDf2Q9Rae7Hkuz61fgVNv5blznycnIqfD2ryzUgIWxUnhbmujOG870ald/p5Byv+SUcYpKRQniU6tokvxFwQb42jpOpi777kVnUaNNW8VhTWBm4Xhp59O7xlX43a5qCgqpPjQbqzWDahVGlTqSvDsR6MFa3MCbslBqW03wxqHU5ZURnafYbQuKqN3hI/D1SXIAuyvr0ColTjYzYAvNIzUy1ZQMX8gqWVWYmsrKEhrZrdLx9BhnzAUOOTS8IU9luiQGB7e/jxwTnv9vaLARqNMjFumRhf4npjXmsy1oeXcnzsFj6eJrdtuoaKilHuGjqRr1h1o1MafaQnFn6Wk2zsOyv3371NbdISqwwfIGjyc0Nj4jq6OQqHoYOfd/wiCIDJlzAD0Oi2CKHLWS4tI7xKYI6j55ffYPuMcDtx1O7qyUlpbXezJG8+E8UuZMnkd3XuvYd3ai8iOfphNl33GTfpn0fgNXDB9ChWHm5AEcBQZOXvxPAC8Kj99b7oC5+BZ9GiqpPLID6RdWYbz0vn4zBH0PNDKGbaDGNsCbx911XuZFVyOs+kQu8rtP3sMVpUXgCyxjEXd9TzYayouVzkrV11CY2M148c9To/sh5Rg5SRSeliOg3LvfXxkSaJwx1bC4hNJ/dPZZ/9CMspJVihOooSMTEJjQ8lbvJrskWPbP9cWFCIiYdIboaQU/Z791GzdzhcXXcbBnkPJW7ONaI0K9f5DTF+1jsp1B/j0iyXYVaMQEUh0NDA6Vc32Vg0hBXa8/sB0Len9TmdQ7gQMxjM4kvcp6mUPIve8BFPyRORrDmPd9iT6VS8yeLuH/VlB1ETrSdTJXG4R2LnDgq1yKc2hwSTm9GNvbRVVkhaXVscF5moeGXY2apUeq3UXq9fchV6vZ/y4NzEYkjqqeU8ZSsCiOCGaqipoKC8ltWffk/j68UmijGFRKE667NFDWP/Jd1QfOdyeS0lwOpENanI+/BBTTCzbRgyD4GCKoxKoDI1CdNnZ5xU5raGB6LpaXImhaA4fpLH7KAA+fbMaAC3gQ0AMuZaBRpnY6hCW3LMJ1bACUodcR+7yJ6koXUNC6mgEUSRk4L2sq2pj+O45FOjSCaYCAJMpMOjW7G7DXNOGWPUNPUWRQcYWsrI20KUsDeRplJW9y9atHxEVHcvgQS+j0SgTp/4VlEdCij9FliSObNuM3+cjc+DQf16wcpSSLluhOLkyBw/HYNKyZM7b2BrqABj80isgwI65L+NqaUbb1IIqIZ4GnZHpnma2TRrGkQmD+Nf8d1HJMu5BvRn03btceE93+nWxMjqonKlBEpPNIsPbDjKquw+DSk+jT6LWI/KfhkX8Z8ciABLePwveOg1s1ezev4pBe+ayLedKmmN/zMyurTUw+/SpTO/alRFBQaT5/QwKCubf1zxChi+H2oQdfL1oMps3f0BGxgCGDnlbCVb+QkoPi+IPcznsFOftIL3vwH9soAIgS8rkhwrFyaZSqznrntv4/L4nmH/nQwRrDFiiY5AFgR2H9qK/4HyCfX5sI0djDbbwJTBwYxEJwXp0vfoSnreDbp/NY7nLxfRnHic9OgRnYwSyuwVv0wHC4obwX7OWjJEt9K3yMsKoITF0Is+XvfdjJSq2If+nGz2RORTWk55nPEb9+j7ti01SErH9+hLb79g0Fp7yclyf2nFFJ5E8JpbuU55UHgF1AKWHRfGHtNTWUHloP12HjPhHBysAsldC0P41SeoUilNZUGgYky68gghTKrKspbxkPwAqUUuI0wJA25wf5527023jooY6zpl9GzuHjgIgccNatj77LG15tQCEXZzFN1MDyUlrdA7uD47mdotE+ozhnD71Zl60PM1+OaW9TAEZn6Ai4oIP2VW/Cx2BLLzJtnPoPuXtn9RZcrvZd/sdeH1+xv37DfpO/1gJVjqIErAofrfGijJs9XV06TuwUzxKkT1+BK3yq6BQ/BVihnZjyh3XkBo1iHGDruXmj7/irNhzMPa7Gt3oy4hxOFl17QVU9sugeGgOl3oDCd4sxYUAGJqbCH7/EwRtAgDa5BjMJXa8Apwbn0xWXTX7o+N57fsVOBxt7FrTyK6Ku2i9dAffh47Ch4q9E94iIjKZ/Jof5ytKmXg/ekvsT+pb+cyzNDU10euJx9Gl/4NeJuiElG9pxe9SW3QEd1sbSTm5HV2VE0b2SAgapYdFofiraBOC6TVrBBUVldR8so+4h85A1NehMQ/EOOwOjMMvQBVswqBV89jYrnygMVGSkU2bwYDxjdfxn3dNe1kFn21g+pV90MjQ+4cqPhzWh+mVxTwVEkOXrfncdUE2jQPj0CalcXnuw2QM+56n69P5smArcdYP2svJX7eWloZmrA3NtLU68Hl9tK5cyYG1a+l18cXou3XriKZS/A9lDIviuMiyTHHedoLDIoj+J72yfBxkrx9R6WFRKP5S+oxQep09hB0L1qMx64l/7AJsK3ZhWyaCOqh9vYIt+9i1/FuIjSLqky9JyErm4zXLaCr5gQkJl2Mo1qMXJRpE0EmAaODVmdMYu34L13t1AAiZMXzxwPN8M2owXwuRfGKq5azyO46t0I23UP3/DWari4wkoms24TOVue3+DpSARfGb7M1NVB7aT0rPvuiMnS8pkuyVQK0ELArFXy2oTww97QPI+2ELvcx6zCNysS3biKANxWVv4Z0Pb6SxIYk4bTxnX3IelvhwvpnzPLV7dtA3fBwmdQjuwSIrFywlWwrjX30MnGUv4vmvmqgxhwEQ2tKE8M0XVDtKqS5Ygy8+k0embEYruInO/JDa/IuptKbhGDuApFVfU3/VzaBS8V1eCVqdyN2P3tQpHn13BkrAovhFPq+Xsn15aHUGsgYP7+jqnFTKF5JC0TEsI5LIsbnZvWwrfcw6DD0iaNtbz/Yl55OVVUBzVBFnnL4crc4AQGrPvjh3VpNuDrzd01DTTI/iMBakHWJ7aCIbKmJQGXQgS2TXVzFq9Ro8jnJGXHwbq778mBFjvkMr+Kjz55B34CsiRZHuPZ6g37T+wOMAPL/0ELtrRZ6+cgqhEcqkqH8XSsCi+Am/z0fZ3jxkZJJyeqHWaDq6SgqFohMLn5JOps1N3hcbSAzWosZCcEsuXnMXQkN/YNPmhxg58mkAVA06hkQFZkH2GSG+OISV5q2MGT6S86LjGb7ycdTeSi7QpHFZ91mET7yXDfM/Zu2Hz6EC8ituISXzC8KEg6hV+6j0nc+E9B/nO9tU2MjXa7YzfVR/BqSGdURzKH6BErAo2vk8HsoP7EWWJJJyeqLWaju6SgqF4hQgCAIx52VTV7mOsuZIQrusJHvmY4gaNUuWngvaBSxZmk9y3B3s2L6TUQQG/duNzSxL38NC12JatrzPVO041o65g2sXXkLz/l18/vnhY/bjFVR41yyh3DqZgeP7UNO2kXOH/at9eZPDwwOfrCUpPoYbxmb9pW2g+G3Kg3sFTVUVFO7YQsWh/SR270Fan/6nVrCiPA5SKDqcoBLoduN5aIYupNBfRf7h5xEEmbFjPsTnzUat3kNl3UyqDPmoroijJbaFoLogzt0zkg9S/stNEbNZ4VrH9O/PYcRqE4n1RiIG9yQkKprQ2HhmPv1fLvzPW7jT+uHauZwVT/+H1rJuGLSBR02yLHPnp9sQJS/PzRyGSlS+F/5uBFnuHBOp2Gw2QkJCsFqtmM3mE1p2Sd4OUnr1/e0V/0FcdjtVBQeRJYnQ2HjC4hI6ukodxpXfjD5TSa+tUPwdyLJMeel77Fq6gaguBvqNeBSVGMSyHwaiNrQQF/oK3XpPBKBm60F8XzYENpxoZm2hlb2NHxGxowqAlAv/TVJiLA31jUyaMKJ9H2u37mP5O68R0lyCO2Mw/773Vj7ZXsVHi9dz38XjGdst5i8/7lPZ8V6/lYDlOHSmgKW1sYGaogIMpmDiunZDFJX8I0rAolD8/TQ1bWDzd2+hUonIxj2og5uIMtxM7pAbjlmvfOVOhKUOFoh2/itJdEPFJSN1HFo4H5O1Aj8iKiQcocmcMftaevXOAUCSJN5882OsKz/HbopiS9Rghg3qy/1n9eqAoz21He/1W3kkdDz+4Y8MHC3NHNm2maJd22izWUnvN4iE7jlKsKJQKP62wsKGMvqcx9AF+3DV9aRmYw7RsZN+sl78iJ7kd3mfFyUJCdiPn1WNZu577VVSZlyDP2Mg0WdeidRmZelT9/DKnHfx+yVEUWT27IsZeO3dBHlb6Okp5s7TO09CzM5I6WE5Dv/UHhaX3U75/j2YQsOIzchSXt39BUoPi0Lx9yXLMqvmPU3lLhsup5fknFTSk3rjabbjb3Yj2X1o5FqEtmSa/GqCRImaJB2jLhuKRvvjeyV2h4tXnnkB9aEN2KKymH3fPcRGhfHty89x+OBBLr73EaITTt1H4x1JeSR0Av3TAhZZlinfvxdZDrztowQqv04JWBSKvz/J72fX4m9oXd9GsBBMtGzBI7lwCy6CBQsAnu4V1LWIxFbFUqERiLkgiy7do44pZ+GiJRz87E38opqMwSMo2bWJqbMuI3vEmA44KgUoj4ROWY6WZvI3byAiKZnkHr2UYEWhUHQKokpF39PPot+lp2GS9ZSK9dQbXUQMzWxfJyxyEANvnIH1nHTUkozwwSGWv5uHzye1rzPtrAmc/8RLeI2hlG5bS2LXHCVY+YdQeliOwz+hh0WWZUr37EKl0ZDYvUdHV+cfRelhUSj+WWRZxlvtwLqlksM7DxATFoXRoUKye1FZdERcmYPPqGH123lkVzop1Qn0uL4PligTAF6/xAVzVhBUf5j/3nUZ5iBTBx/RqU3pYTmBvG43TVWVHV2NX9RSW0PB1o3EZmQpwYpCoej0BEFAGxdE5LQseozuQ31TPTF39cc0KBZ/i5va53fg2VzNpBv7UzkxkVQ37J63n/+7P//vinwa62r519UXKcHKP4gSsByHjIFD8LpdHNm2Gb/P19HVaSfLMiV5O3C12sgcOBSdUfnF+0M6RyejQnFK0ncJRfbLeCsdhJ6VTuQNvRANalqXllL7ah4DBidyIFRNlxo3q57cxPKtFXy9ZjtnjuxH7ySlZ/WfRAlYjlN0ahdSevWlaNc26kqKOro6tNmsHN64lpj0LGLSM397A8UvU8b5KBT/WNr4IASViCu/CQBdQjAx9wxElxWKt6yVmie3MuqynhwZGkWCzUfEwt30CI/khrHK9+Y/jRKw/A5qjYaM/oPR6HQc2baZhrKSv7wOsixTcXAf9aXFZA0ZgT4o6C+vg0KhUPxdCGqRkFAL9QVV7Z+JapHIy3LQdwtDdvmxLSlh1NQsjLnhOAQ3d00fiFqlXP7+aZTJD/+A0Nh4QmPjaa6p4si2zQRHRBKd2uWk7rO1qYG64kJAIDY9E2OI5aTuT6FQKP4JZL9ES0MT3Ub2+skyVYgOAE+pDeehJkr2HyLntL5YUix/bSUVJ4QSsPwJoTFxhMbEYauvo2jnNgAMZjMxaRkI4p+P3n0eDxWH9uP3egkKDSOtzwDlNWWFQqH4H4JKJCIqggNrd5Ebqid4QGz7stCz0hG0Iva1lRS9vw2LxULIiKQOrK3iz1AClhPAHBmFOTKQnKjN2kLJ7p3IsoxKoyEusysanf64ypFlGVt9LY2V5SCDqFaT0DX71Jo5WaFQKH6njOuHEPzxPvZ/s42BvacgaH6cdsQyOQ1ZkineuIs+44cjqJVHQf9USsByghlDLKT27geA1+OmOv8wfp83sFCW2wd4qrVa/B5P+3by0eXmqGhSe/VTelL+IrKkvCGkUPzTCRoVEadnUvxCEcWvbSUo2oKgVWEZHI9oUHN4234yenfH1Du6o6uq+BOUgOUk0mh1JOX8dDItWZbxeT2oNVolMOlofkm541IoOgFNhIGeFwyj+Ie9NBW14Hf58G3dh1FvQK1SETUlo6OrqPiTlIClAwiCgEar6+hqKADZKyFolIBFoegMTDmR5OQE0uzLPom2vQ2ULztA4qRsRKOmg2un+LOUgEVxSpN9MqiUXi6ForMR1CLGnHCSjbkYssI6ujqKE0C5tVSc0mSf0sOiUHRWroIW9OlKNtvOQvmmVpzSZJ8yhkWh6Iz8Di+iXo2g9KB2Gso3teKUpgQsCkXn5Cm2ok395Zl/Ff88yje14pSmPBJSKDofX4MTVZheeQuzk1G+qRWnNNkrIShziigUnYq3rg1tnDLPWmejfFMrTm1+GdTKXZhC0Zko41Y6JyVgUZzylG5jhaLz8Du8Ss6VTkoJWBSnNllJza9QdCbeSjsa5XFQp6QELIpTm9K7olB0KrIkK4+EOiklYFEoFApFpyD7ZeUepBNTAhaFQqFQdAruYivalJCOrobiJFECFoVCoVB0CrLHj6hTdXQ1FCeJErAoFAqF4h/Pb3OjMms7uhqKk+h3BSxz584lNzcXs9mM2Wxm8ODBLF68uH15TU0NF198MTExMZhMJvr06cMXX3zxq2U+9NBDCIJwzE/Xrl3/2NEoFAqF4pTkrXYobwd1curfs3JCQgJPPfUUGRkZyLLM+++/z5lnnsmuXbvIzs5m1qxZtLS08PXXXxMREcG8efOYMWMG27dvp3fv3r9YbnZ2NsuXL/+xUurfVS2FQqFQnOJkGQRRGXHbmf2uyGDq1KnH/P3xxx9n7ty5bN68mezsbDZu3MjcuXMZMGAAAPfddx8vvPACO3bs+NWARa1WExMT8weqr1Ao/ip+uwdvpf2v3akggEDgh8D/C8L/fn70AiUcTQAo/H/b8T8XMeHYzwHwy8g+Cdkvg//onyc6Nc//5foRBRCFQH1EAUEtIqgDf6IWEVT/95kIKuGYhIayJCN7JWSfhMqkJEX7/8n/r717j23quuMA/r1+20mcF3nwbAGTpEBDN6p1QZ3GCnQDigpUKysI1g51dGNdt9ExsnVj/NFRbStVBVvJ1qlNp00UqEAdYyAqKGWD8gxtCOWV8gokISGJ7ST2te+9Z38EXEKCiRNfx7G/HymCXF8fn8PP+P58zrnnaFxPKRn0uitDVVVs2rQJbW1tKCkpAQBMmjQJ7777LmbOnImMjAxs3LgRfr8fkydPDlvW2bNnMWTIENhsNpSUlGD16tUYMWJE2OfIsgxZlkO/ezye3jaFiHogcNkL+33ZMXs9IW5JHm7+XQCA6MgBBL5IBm78XXQ5duP4LeeE/pQkSFYJMN5IFow3EgUdvqWH2qKJjourdiNRUjr+hE+BdiNxEorWsWXEF0/uqKvFgODVNqROGhL1+g10yrV2mPNT+rsapLOIE5bKykqUlJTA7/cjNTUVW7ZswdixYwEAGzduxLx585CdnQ2TyQSHw4EtW7bA5XLdsbyHHnoIb7/9NgoLC1FbW4tVq1bha1/7Gk6cOIG0tLQ7Pm/16tVYtWpVpNUnol4QNy6asdSpxwSdX3ugdfyH2mKQ+lR3rTUYrSolFMUtw5bn6O9qkM4kISJbmzwQCODSpUtwu93YvHkz3nzzTezduxdjx47F888/j0OHDuF3v/sdBg0ahK1bt+K1117Dvn37cP/99/eo/JaWFtxzzz1Ys2YNFi9efMfzuuthGT58ONxuN5xOZyRNoiTmP9MMW0Fmf1cj7smXPDBl2HgXRj+SL3pgTLfAlGHr76rEHd/pJtgLs/q7GtRLHo8H6enpd71+R9zDYrFYQj0mEydOxOHDh/H6669j+fLlWLduHU6cOIFx48YBACZMmIB9+/bhT3/6E9avX9+j8jMyMlBQUIBz586FPc9qtcJqtUZafSKKkNoagNYWhHEEvwj0JyGrTFYoqfV5HRZN0yDLMtrb2zsKNHQu0mg0QtO0HpfX2tqK6upqDB48uK9VI6I+EpqAXO2O6dwVokiorQEYuTtzUogoYSktLcVHH32ECxcuoLKyEqWlpfjwww+xYMECFBUVweVyYcmSJTh06BCqq6vx6quvYteuXZg9e3aojClTpmDdunWh31988UXs3bsXFy5cwP79+zFnzhwYjUY89dRTUWskEfWOfN4NWyGHzOKBEIJ3w3QjUNMK8zCuv5IMIhoSunbtGhYtWoTa2lqkp6ejuLgYO3fuxLRp0wAA27dvx4oVKzBr1iy0trbC5XKhvLwcM2bMCJVRXV2NxsbG0O81NTV46qmncP36deTk5ODhhx/Gxx9/jJycnCg1kYh6QwgBIasw2LguUjyw3uOE/HkLbC4mkJ3cvKWdEl7Ek27jVU8n7RDdyn+6CbYBMFlPaAKBCx6IoNpxQJJCt+uaMm0w5dij/qEdqPHCmGaBMZ1zxeKF7+R12MdyeO4moQrI55oHxP9hujPdJt0SUWwJIeD7pAG2sdldNnYTQkBt8sN/pjm0ZokxzQLL0L53kaueACzD7ry0APUDDgl1ErjkgWU436PJggkLJbcB0JXsP3kdtvuyut2FVpIkmLLtMGXbQ8eC19oRuOzt0we54uZGcvEmUOPlXjm30doVGDjhNmkwYSECEGz0QbnuCw2rWO5xxsU29fIFN8yDUyOaR2LOdUD+vOXG7rW9G84JXmnl0EOMBWrboDb7O+ZkmI2wjk4PvR+VFj+0doU9XrdQrvtgGsTbvJMJExYidCztffMCLVQB+bwbIqDCPDQVpn6awyEUDZpfhfXeyD+UraMy4PvsOuy9SFiEKiAZ47/nKdEIWYH1XicMDjPUtiB8lY0w2EwQigZDipkLHN4mWN/OpDrJMGEhAjo2nLv5d6MEmysDQMcKr0p9e79cLPznWkL16BWDBKFqHXvkRPK6Z5thvZcT12PNMvzGXUBjMmFMMcNRnAOhCe5A3A0hRMdmkpRU+rxwHNFAp7TIMKR2Pw5uHeGEeUgKfCcau31cd33o6bCNyoDvZFNEz/FXt8CUZeOtzP3B0NGrdismK91TrrXDnMu9g5INExZKesHaVpgH33mnV2OqBZZ7nR134sSQOccOpdHX6+dLZgOs9zjR/mkDNFkNe64QAr6q6zBl2Xgh6CdcS6Tn1BYZxkzebp9smLAQSdJdLxbGVEvMVxk1ZtmgXPf3rQynBfbxgxC46IHvVFOXb/BAx5wV36cNsI5OhymTkxj7kynTBqWpbzFPFkzwkg/7fSlpCU1AiJ7NEfCfboIx5YthIyEElEYf1Ba5Y20MkwGmLBuM6daodeNH6wNZMkiwFWRCKBr851oACbCOTIfBYoTqDUCuboF9/KBO83iof5jzU+D7rKOni4g6Y8JCyUvVoFzzwfFA+G0gAjVemPIcMGXYIBQNcnULhCpgznPAOiodktEAEVShNMuQz7V0DMWMTI9OHSVEbeKlZDLAXpQFEdQgX/IAqoBkNcI+IYffVuMM79Qi6ooJCyUtEdQgZAXGtPALpElmA5RrPijXOuaTWEdlQDIbbjvHCHOuA+ZcB3wnr3f03EQhCbAMTkWwti0qK9feJJkNsI3OiFp5FF02Vwb855ph53Lz3RKKxjuEkhQTFkpaQu3ZnBRzXgrMeXeelNvl/PwUKA2+qExeNTotCFxt7XM5NHBIZiMkowGaT4HBzo/o2wVq+raKMw1cHLSmpGVINSP1a8OiXq4x09qnu3uIrKPSIV9w93c14pLGHcSTFhMWSlqSJOmy/L4kSTA4TFCuRydpMdiM0HxKVMqigUEySBz2ILoNExYiHVjvTYfSIkO+6OlzWZZhaQjUeKNQKxpIOBG6K6FoXEwviTFhIdKJbXQGjOkW+M/2bcE5yWSACIRf+I0SkOi47Z6+EKxrC7vIIyU2JixEOjJl2DrWablB9QYQqPFGvAid0WmF2hqIdvUojkl2E0QPhgIDtW3wn22O6rChJisINrQjWN8GrT0YN4mT1q7AkNL9NhqU+DhziUhnN+9GCtR4IVQBU5YNvk8aYH+g5+ufqG1BmPO5ZH4yMWXaEGzwwXpP9xdooQn4T16HKT8F1lEZkKtbYMy0wpzTu/dJsKEdSoMPMHTM7TKmWwGzhGCjD8KnQACAAEyZVphyHf0zZBWl5QJoYGLCQqSjYH1bxwc/ALU1CHtRx9oaVlcGgldaYRl299szg3VtMKaaIZmjP0GY4pcxzYJgbRtUTwBGZ+e1gjS/Av+pJtjuyw5NHLcVZMJ3uqnHCYsIqghcbQv1zJiybbCPze5ynimj8549SpMf/tPNgCZgHZXOO3YoZvhOI9KR2hqEOc+BYH1bpw9+TVa7LD7XHaXJD7UtyIXekpStIBP+M80IXG2FJCHUyyGZpC4rFCvXfTCmdr8IolAFgtfaoXrk0DHJZIBlcAoMjsiGWExZNpiybB0bZh5vgL04J2ar8sbHwBT1FyYsRDqyjkpH4KIHktEQWuxKaw9CqWuDffygsM9VvQEE69q6/dZLycNWkNmj84J1bbCNzYbqDUBp9EEE1NAFXpIkmPMcsERxwqokSTDlOqC1B++6WnQ0aH5Fl2UIaOBgwkKkI0mSYL03HUIIBOvaoDT7IZmNsI0Ln4TIF9wQimCyQj1mynXAf6oJRqcV5iGpMbm4G1LN0Npik7AErrTCOoIr3CYzJixEOhNCoP3YNVhHpsNWlNXtpMGOhKYdqrujy96cn9Jl7gBROOYcR68n3PaWZDJAjdEt90LROI8ryTFhIYoByWJEoMYLQ0M7NJ8C89BUqJ5Ax0ZuN/rtzfkOWAZzwzsaOALn3bCxF5BihAkLkc4kSYLj/i/mqwhVQGn2wzoijd8YacAKNvpgzLLFZOVZzl8hgAvHEcWcZJRgHmRnskIDltAEgrWtsAxJjcnrBS5zh2ZiwkJERBHyn2mGrSB2w5dCFZCMvFwlO74DiIiox+TzbpgyrTEbohGq4IaHBIAJCxER9YAQAr6qRhjTrTDnxW4DwkCNF5ZhsRl6ovjGSbdERHRXvk8bYCvMivlS/JpPiXg1XkpM7GEhIqKwVLcMU44j5slKvOwSTfGBCQsREYUVrG+HOT92w0A3KfXtMOdyl3LqwISFiIjCE/0z8VVp9MGUZYv561J8YsJCREThdbOdhN7kix6Yh3HtFfoCExYiIgovxnNJVG8AIqByPy3qhHcJERFR3FBa/AjWtcNexH21qDMmLEREFJZkNUKTFRis+l4yAjVeaLLKZIW6xSEhIiIKy5Rlg3Ldr1v5QhPwnWiEZDPBNjpDt9ehgY09LEREFJbBYUawwadL2apbhnzRA/t9WdwQlMJiwkJEROEZJYiAGvVi/dUtkAwSHMU5US+bEg8TFiIiCkuSJCCK67CobUHI51pgHZ0OY6olauVSYmPCQkREdxWtdCVwtRVaWxD24kEdiRBRDzFhISKisIQqotLDErzWDhHUYBuTGYVaUbLhXUJERBSW0tD3PX2UZj9UTwDWe5xRqhUlGyYsREQUluqWYXD2fq6J2hpAsK4NNldG9CpFSYcJCxERhSdJvZ5vovkVyOfdsN+XHeVKUbJhwkJEROH1ci8hoWjwn2qCffygKFeIklFECcsbb7yB4uJiOJ1OOJ1OlJSU4D//+U/o8bq6OixcuBD5+flISUnBl7/8Zbz33ns9Lv+VV16BJEn4yU9+Ekm1iIhIRwKAiDBpEaJj9Vr7/Tm8G4iiIqKEZdiwYXjllVdw9OhRHDlyBI888ggef/xxVFVVAQAWLVqE06dP4/3330dlZSXmzp2LJ598EhUVFXct+/DhwygrK0NxcXHvWkJERLow5zigRLjSrb/qOmz3ZUMyMlmh6IgoYZk1axZmzJiBMWPGoKCgAC+//DJSU1Px8ccfAwD279+P559/Hl/5ylcwatQovPTSS8jIyMDRo0fDltva2ooFCxbgr3/9KzIzebsbEVE8MWXZoDT2PGHxn22GZUQaDFYutU/R0+s5LKqqYsOGDWhra0NJSQkAYNKkSXj33XfR1NQETdOwYcMG+P1+TJ48OWxZS5cuxcyZMzF16tQev74sy/B4PJ1+iIhIH5LVCM2v3PU8/7kWGDNtMDqtMagVJZOIF46rrKxESUkJ/H4/UlNTsWXLFowdOxYAsHHjRsybNw/Z2dkwmUxwOBzYsmULXC7XHcvbsGEDjh07hsOHD0dUj9WrV2PVqlWRVp+IiHrBOjId/jPNsBdl3fEc/5lmmAbZYcqyxbBmlCwi7mEpLCzE8ePHcfDgQfzgBz/Ad7/7XZw8eRIA8Otf/xotLS344IMPcOTIEfzsZz/Dk08+icrKym7Lunz5Ml544QX84x//gM0W2Ru8tLQUbrc79HP58uVIm0JERD0kGSTcae6sJito/7QB5nwHkxXSjSQinfp9m6lTp2L06NFYvnw5XC4XTpw4gXHjxnV63OVyYf369V2eu3XrVsyZMwdG4xfjnKqqQpIkGAwGyLLc6bFwPB4P0tPT4Xa74XRyJUUiomjzn2mGraDzPMNgfRuUFhm2MZmQorhBIiWPnl6/+7yXkKZpkGUZ7e3tAACDoXOnjdFohKZp3T53ypQpXXpfnnnmGRQVFeEXv/hFj5MVIiKKgdu+3ypuGWprEPbCOw8TEUVLRAlLaWkppk+fjhEjRsDr9eKf//wnPvzwQ+zcuRNFRUVwuVxYsmQJ/vjHPyI7Oxtbt27Frl27sG3btlAZU6ZMwZw5c/CjH/0IaWlpGD9+fKfXSElJQXZ2dpfjRETUv4QAhKpBMhqgySqCl71cFI5iJqKE5dq1a1i0aBFqa2uRnp6O4uJi7Ny5E9OmTQMAbN++HStWrMCsWbPQ2toKl8uF8vJyzJgxI1RGdXU1Ghsbo9sKIiLSnc2VAd/J6zDnpUBp9ME2lsvtU+z0eQ5LvOAcFiIi/Sktfqhu7rpM0ROzOSxERJQ8TBk2mDJ4JxDFHjc/JCIiorjHhIWIiIjiHhMWIiIiintMWIiIiCjuMWEhIiKiuMeEhYiIiOIeExYiIiKKe0xYiIiIKO4xYSEiIqK4x4SFiIiI4h4TFiIiIop7TFiIiIgo7jFhISIiorjHhIWIiIjinqm/KxAtQggAgMfj6eeaEBERUU/dvG7fvI7fScIkLF6vFwAwfPjwfq4JERERRcrr9SI9Pf2Oj0vibinNAKFpGq5evYq0tDRIkgSPx4Phw4fj8uXLcDqd/V09ug3jE98Yn/jHGMU3xqfnhBDwer0YMmQIDIY7z1RJmB4Wg8GAYcOGdTnudDr5ZoljjE98Y3ziH2MU3xifngnXs3ITJ90SERFR3GPCQkRERHEvYRMWq9WKlStXwmq19ndVqBuMT3xjfOIfYxTfGJ/oS5hJt0RERJS4EraHhYiIiBIHExYiIiKKe0xYiIiIKO4xYSEiIqK4N2ATlmPHjmHatGnIyMhAdnY2vv/976O1tbXTOT/+8Y8xceJEWK1WPPDAAz0q1+/3Y+nSpcjOzkZqaiqeeOIJ1NfX69CCxNaT+Fy6dAkzZ86Ew+FAbm4ufv7zn0NRlLDlnjlzBo8//jgGDRoEp9OJhx9+GHv27NGzKQlJr/gAwL///W889NBDsNvtyMzMxOzZs3VqRWLTM0YAIMsyHnjgAUiShOPHj+vQgsSmR3wuXLiAxYsXY+TIkbDb7Rg9ejRWrlyJQCCgd3MGhAGZsFy9ehVTp06Fy+XCwYMHsWPHDlRVVeHpp5/ucu73vvc9zJs3r8dl//SnP8W//vUvbNq0CXv37sXVq1cxd+7cKNY+8fUkPqqqYubMmQgEAti/fz/Ky8vx9ttv4ze/+U3Ysh977DEoioLdu3fj6NGjmDBhAh577DHU1dXp3KrEoWd83nvvPSxcuBDPPPMMPvnkE/zvf//D/PnzdW5R4tEzRjctX74cQ4YM0akFiU2v+Jw6dQqapqGsrAxVVVV47bXXsH79evzyl7+MQasGADEAlZWVidzcXKGqaujYp59+KgCIs2fPdjl/5cqVYsKECXctt6WlRZjNZrFp06bQsc8++0wAEAcOHIhK3ZNBT+Kzfft2YTAYRF1dXeicFYwKrgAABc9JREFUN954QzidTiHLcrflNjQ0CADio48+Ch3zeDwCgNi1a5dOrUk8esUnGAyKoUOHijfffFPfBiQBvWJ00/bt20VRUZGoqqoSAERFRYUu7UhUesfnVr///e/FyJEjo1f5AWxA9rDIsgyLxdJpkyS73Q4A+O9//9vrco8ePYpgMIipU6eGjhUVFWHEiBE4cOBA7yucZHoSnwMHDuD+++9HXl5e6JxvfvOb8Hg8qKqq6rbc7OxsFBYW4p133kFbWxsURUFZWRlyc3MxceJEHVuUWPSKz7Fjx3DlyhUYDAZ86UtfwuDBgzF9+nScOHFCx9YkJr1iBAD19fV49tln8fe//x0Oh0OnFiQ2PeNzO7fbjaysrCjVfGAbkAnLI488grq6OvzhD39AIBBAc3MzVqxYAQCora3tdbl1dXWwWCzIyMjodDwvL49DDhHoSXzq6uo6/UcGEPr9Tv/WkiThgw8+QEVFBdLS0mCz2bBmzRrs2LEDmZmZOrYosegVn88//xwA8Nvf/hYvvfQStm3bhszMTEyePBlNTU16NSch6RUjIQSefvppPPfcc3jwwQd1bEFi0ys+tzt37hzWrl2LJUuWRLH2A1dcJSwrVqyAJElhf06dOoVx48ahvLwcr776KhwOB/Lz8zFy5Ejk5eWF3Zqa+qa/4yOEwNKlS5Gbm4t9+/bh0KFDmD17NmbNmtWnRDVR9Hd8NE0DAPzqV7/CE088gYkTJ+Ktt96CJEnYtGlTtJo5oPV3jNauXQuv14vS0tIotipx9Hd8bnXlyhV861vfwre//W08++yzUSlzoDP1dwVutWzZsm4nzt5q1KhRAID58+dj/vz5qK+vR0pKCiRJwpo1a0KP90Z+fj4CgQBaWlo69bLU19cjPz+/1+UmimjGJz8/H4cOHer03Jt3Y93p33r37t3Ytm0bmpubQ9u1//nPf8auXbtQXl4e+oaTrPo7PoMHDwYAjB07NnTMarVi1KhRuHTpUq/alGj6O0a7d+/GgQMHuuxv8+CDD2LBggUoLy/vTbMSRn/H56arV6/iG9/4BiZNmoS//OUvvWxNAurvSTTR8re//U04HA7R3Nzc5bFIJ91u3rw5dOzUqVOcdBsFt8fn5oS0+vr60DllZWXC6XQKv9/fbRnvv/++MBgMwuv1djpeUFAgXn75Zd3qngyiER+32y2sVmunSbeBQEDk5uaKsrIyXeufDKIRo4sXL4rKysrQz86dOwUAsXnzZnH58uVYNCNhRSM+QghRU1MjxowZI77zne8IRVH0rvaAMmATlrVr14qjR4+K06dPi3Xr1gm73S5ef/31TuecPXtWVFRUiCVLloiCggJRUVEhKioqQjO0a2pqRGFhoTh48GDoOc8995wYMWKE2L17tzhy5IgoKSkRJSUlMW1bIrhbfBRFEePHjxePPvqoOH78uNixY4fIyckRpaWloXMOHjwoCgsLRU1NjRCi4y6h7OxsMXfuXHH8+HFx+vRp8eKLLwqz2SyOHz8e8zYOZHrERwghXnjhBTF06FCxc+dOcerUKbF48WKRm5srmpqaYtq+RKBXjG51/vx53iXUS3rEp6amRrhcLjFlyhRRU1MjamtrQz80gBOWhQsXiqysLGGxWERxcbF45513upzz9a9/XQDo8nP+/HkhxBf/Wffs2RN6js/nEz/84Q9FZmamcDgcYs6cOXyz9EJP4nPhwgUxffp0YbfbxaBBg8SyZctEMBgMPb5nz55O8RJCiMOHD4tHH31UZGVlibS0NPHVr35VbN++PRZNSih6xScQCIhly5aJ3NxckZaWJqZOnSpOnDgRiyYlHL1idCsmLL2nR3zeeuutbq9ZCTQY0ieSEELEdhCKiIiIKDK8pYaIiIjiHhMWIiIiintMWIiIiCjuMWEhIiKiuMeEhYiIiOIeExYiIiKKe0xYiIiIKO4xYSEiIqK4x4SFiIiI4h4TFiIiIop7TFiIiIgo7jFhISIiorj3fzb9qToAN6xvAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mVAPt2 = 0.45\n",
    "print(\"and now the vtds in mear-StLouis counties with vtd mVAP >\",mVAPt2)\n",
    "cList = [91,95,114]\n",
    "mVpop = 0.\n",
    "for c in cList:\n",
    "    plotPoly(countyGeom[c],2)\n",
    "    for t in countyTractList[c]:\n",
    "        if tractWhiteVAP[t] < (1. - mVAPt2)*tractVAP[t] :\n",
    "            plotPoly(tractGeom[t])\n",
    "            mVpop += tractPop[t]\n",
    "        else:\n",
    "            plotPoly(tractGeom[t],0.1)\n",
    "plt.show()\n",
    "\n",
    "print(\"Now draw a box approximately around the near-St L high-minority area\")\n",
    "ptXs = [-90.4, -90.35, -90.1, -90.1]\n",
    "ptYs =  [38.95, 38.65, 38.65, 38.95]\n",
    "pts = [Point(ptXs[i], ptYs[i]) for i in range(len(ptXs)) ]\n",
    "VRApoly = Polygon(pts)\n",
    "ptXs = [-90.4, -90.35, -90.1, -90.1]\n",
    "ptYs =  [38.95, 38.65, 38.65, 38.95]\n",
    "pts = [Point(ptXs[i], ptYs[i]) for i in range(len(ptXs)) ]\n",
    "VRApoly = Polygon(pts)\n",
    "plotPoly(VRApoly)\n",
    "coreVTDs = list()\n",
    "for c in cList:\n",
    "    for t in countyTractList[c]:\n",
    "        if VRApoly.contains(tractCP[t]):\n",
    "            coreVTDs.append(t)\n",
    "c = 114\n",
    "for v in countyTractList[c]:  #on second thought ...\n",
    "    if v not in coreVTDs:  #since 'county' splitting is discouraged, force all of St Louis into the VRA core\n",
    "        coreVTDs.append(v)\n",
    "corePop, coreVAP, coreWhiteVAP = 0., 0., 0.\n",
    "for v in coreVTDs:\n",
    "    plotPoly(tractGeom[v])\n",
    "    corePop += tractPop[v]\n",
    "    coreVAP += tractVAP[v]\n",
    "    coreWhiteVAP += tractWhiteVAP[v]\n",
    "for c in cList:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "print(\"the core pop is\",r5(corePop/aDP),\"of a district\")\n",
    "print(\"its mVAP fraction is\",r5(1.-coreWhiteVAP/coreVAP))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2e8128ef-0a77-40a5-8c75-766d96f9a1f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now define the envelope of nearby vtds that will include the core in their adjusted HD\n",
      "  Do this by expanding a circle from the centroid of the core until it captures sufficient pop\n",
      "final envelopePop/aDP, corePop/aDP are 0.21042 0.79285\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now define the envelope of nearby vtds that will include the core in their adjusted HD\")\n",
    "print(\"  Do this by expanding a circle from the centroid of the core until it captures sufficient pop\")\n",
    "envelopePop, R, toler = 0., 0.01 * VRApoly.area**0.5, 0.005*aDP\n",
    "coreCP = getHDcp([tractCP[v] for v in coreVTDs],[tractPop[v] for v in coreVTDs],[i for i in range(len(coreVTDs))] )\n",
    "dR = 2.*VRApoly.area**0.5\n",
    "targetPop = aDP - corePop\n",
    "availVTDs = countyTractList[cList[0]]\n",
    "for c in cList[1:]:\n",
    "    availVTDs += countyTractList[c]\n",
    "availVTDs = list(set(availVTDs).difference(set(coreVTDs)))\n",
    "while abs(targetPop - envelopePop ) > toler:\n",
    "    R += dR * np.sign(targetPop - envelopePop)\n",
    "    dR *= 0.5\n",
    "    envelopePop, envelopeVs = 0., list()\n",
    "    coreCircle = coreCP.buffer(R)\n",
    "    for v in availVTDs:\n",
    "        if coreCircle.contains(tractCP[v]):\n",
    "            envelopePop += tractPop[v]\n",
    "            envelopeVs.append(v)\n",
    "plotPoly(coreCircle)\n",
    "for v in envelopeVs:\n",
    "    plotPoly(tractGeom[v])\n",
    "for v in coreVTDs:\n",
    "    plotPoly(tractGeom[v],0.2)\n",
    "print(\"final envelopePop/aDP, corePop/aDP are\",r5(envelopePop/aDP), r5(corePop/aDP))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f9fbd218-9b05-4883-8dbd-af647772d808",
   "metadata": {},
   "outputs": [],
   "source": [
    "hdCP= [tractCP[t] for t in range(nHDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "72071360-066f-4f3f-8b92-7a55dcfd1ca2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we define HD vtdLists for VTDs in the core and the envelope\n",
      "For core, we grow a circle from HD center\n",
      "For envelope, we pick up all tracts that intersect the line from HDcP to core center, ...\n",
      "...then we grow the district from the midpoint on the line from HDcP to the closest point on the core\n",
      "working on HD 1833 our 0th out of 895 that will contain the VRA core, time = 0\n",
      "working on HD 3022 our 50th out of 895 that will contain the VRA core, time = 18\n",
      "3152 WARNING, circle bisection ran 14 and nonCorePop vs target = 164237.0 159372.125\n",
      "working on HD 3201 our 100th out of 895 that will contain the VRA core, time = 38\n",
      "working on HD 3323 our 150th out of 895 that will contain the VRA core, time = 56\n",
      "working on HD 3561 our 200th out of 895 that will contain the VRA core, time = 75\n",
      "working on HD 3771 our 250th out of 895 that will contain the VRA core, time = 94\n",
      "working on HD 3975 our 300th out of 895 that will contain the VRA core, time = 112\n",
      "working on HD 4113 our 350th out of 895 that will contain the VRA core, time = 132\n",
      "working on HD 4297 our 400th out of 895 that will contain the VRA core, time = 150\n",
      "working on HD 1324 our 450th out of 895 that will contain the VRA core, time = 168\n",
      "working on HD 1236 our 500th out of 895 that will contain the VRA core, time = 187\n",
      "working on HD 1299 our 550th out of 895 that will contain the VRA core, time = 205\n",
      "working on HD 1380 our 600th out of 895 that will contain the VRA core, time = 224\n",
      "working on HD 1443 our 650th out of 895 that will contain the VRA core, time = 241\n",
      "working on HD 2976 our 700th out of 895 that will contain the VRA core, time = 272\n",
      "working on HD 3189 our 750th out of 895 that will contain the VRA core, time = 294\n",
      "working on HD 3484 our 800th out of 895 that will contain the VRA core, time = 314\n",
      "working on HD 3704 our 850th out of 895 that will contain the VRA core, time = 334\n"
     ]
    }
   ],
   "source": [
    "print(\"Now we define HD vtdLists for VTDs in the core and the envelope\")\n",
    "print(\"For core, we grow a circle from HD center\")\n",
    "print(\"For envelope, we pick up all tracts that intersect the line from HDcP to core center, ...\")\n",
    "print(\"...then we grow the district from the midpoint on the line from HDcP to the closest point on the core\")\n",
    "coreTractPoly = tractGeom[coreVTDs[0]]\n",
    "for v in coreVTDs:\n",
    "    coreTractPoly = coreTractPoly.union(tractGeom[v])\n",
    "startTime = time.time()\n",
    "VRAvtdList = [list() for t in range(nHDs)]\n",
    "for jj,t in enumerate(coreVTDs+envelopeVs):\n",
    "    if jj%50 == 0:\n",
    "        print(\"working on HD\",t,\"our\",str(jj)+\"th out of\",len(coreVTDs+envelopeVs),\n",
    "              \"that will contain the VRA core, time =\",int(time.time()-startTime) )\n",
    "    VRAvtdList[t] = coreVTDs.copy()\n",
    "    bridgeVTDs = list()\n",
    "    circleCP = hdCP[t]\n",
    "    if t in envelopeVs:  #HD center is pushed toward core, define the connecting bridge\n",
    "        nearestCorePoint = nearest_points(coreTractPoly,tractCP[t])[0]\n",
    "        bridgeLine = LineString([tractCP[t], nearestCorePoint ] )\n",
    "        bridgeTube = bridgeLine.buffer(0.002) #this assures a connection from HD center to the core\n",
    "        for c in range(nCounties):\n",
    "            if bridgeTube.intersects(countyGeom[c]):\n",
    "                for v in set(countyTractList[c]).difference(set(coreVTDs)):\n",
    "                    if bridgeTube.intersects(tractGeom[v]):\n",
    "                        bridgeVTDs.append(v)\n",
    "        circleCP = Point(0.5*(hdCP[t].x + nearestCorePoint.x), 0.5*(hdCP[t].y + nearestCorePoint.y) )\n",
    "    bridgePop = np.sum([tractPop[v] for v in bridgeVTDs])\n",
    "    VRAvtdList[t] += bridgeVTDs\n",
    "    availVTDs = list(set( [i for i in range(nHDs)] ).difference(set(coreVTDs+bridgeVTDs)) )\n",
    "\n",
    "    targetPop = aDP - corePop - bridgePop\n",
    "    if targetPop < 0:\n",
    "        raise Exception(\"Error, core + bridge pop =\", corePop + bridgePop,\"> aDP\",r5(aDP),\"for HD\",t)\n",
    "    nonCorePop, R, toler = 0., 0.01 * VRApoly.area**0.5, 0.005*aDP\n",
    "    dR = 2.*VRApoly.area**0.5\n",
    "    nLoops, maxLoops = 0, 14\n",
    "    while abs(targetPop - nonCorePop ) > toler and nLoops < maxLoops:\n",
    "        nLoops +=1\n",
    "        R += dR * np.sign(targetPop - nonCorePop)\n",
    "        dR *= 0.5\n",
    "        nonCorePop, nonCoreVs = 0., list()\n",
    "        coreCircle = circleCP.buffer(R)\n",
    "        for v in availVTDs:\n",
    "            if coreCircle.contains(tractCP[v]):\n",
    "                nonCorePop += tractPop[v]\n",
    "                nonCoreVs.append(v)\n",
    "    if nLoops >= maxLoops:\n",
    "        print(t,\"WARNING, circle bisection ran\",nLoops,\"and nonCorePop vs target =\",nonCorePop,targetPop)\n",
    "    VRAvtdList[t] += nonCoreVs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "669e23ed-de67-4a81-a86f-ddd232d1393e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8fd658b8-4a0d-49a5-968c-d0394909b2c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now back to polygonal HD drawing prep ... optional squish\n",
      "for many states we move in outcroppings via clipPoly's before running the wedgePoly solver\n",
      "adding code here to 'push in' state panhandles ...\n",
      "performing squish no 1 for state MO\n",
      "clipPoly 0 intersects [34, 66, 71, 77, 99, 102] counties and a total of 97 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 1 out of 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "performing squish no 2 for state MO\n",
      "clipPoly 1 intersects [1, 2, 10, 37, 43, 73, 82, 112] counties and a total of 62 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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6BRYREakYFXRFyG43ePOnPby9ah83dKjPjFvDqe1mzo+rVbtTmLQwnmBfD5ZP6E2Tup6m1CEKLCIiUlEsOOZjKcelkuz8QiZ/uoWVu1N4rH9rxl/V3JRLL4ZhMGvNfmasSKBPWDBv3N4R74u1eWENocAiIiIVw+IEhh0sZbsR9dDJXEZFx5CUmc9/7+pKnzbBFVxgyZwusPHYki18vTWJB69pwUN9W5nS8VmKU2AREZGKYXF2BBZKH1h+2XOCCQviCPBy54uonrQIMqd54dH0PEZHx3LwZC4zh0dwfYf6ptQh/6TAIiIiFcNi+SOwlJxhGHy09iAvf7uLy1sG8vawzvjWMufSy8YDpxg3P47abs58Pr4nber7mFKHnJ0Ci4iIVIw/LwmVUH6hjSc/38bnm48x5spmPN4/DGcTLr0YhsG8jUd4fvkOLmviz3vDI/D3NKfjs5xbudpaTp8+HYvFwkMPPXRmWX5+PlFRUQQEBODl5cXQoUNJSUkp8Zhjx47FYrHw5ptvlqc0ERGpaqUILEmZp7lt9nq+2ZbEW3d0YuqANqaElYIiO08u284zX2xnRI/GRN/fTWGlmipzYNm0aROzZ88mPDy82PLJkyfz1VdfsXjxYtasWcPx48cZMmRIicZctmwZGzZsoEGDBmUtS0REzFLCwBJ7OI2B76zjRLaVJWN7clOnhlVQ3D+dyLZy54cbWBp7lFdvCedfg9rh6lyu/8dLJSrTn0xOTg7Dhw/nww8/pE6dOmeWZ2Zm8tFHH/H6669zzTXX0KVLF+bMmcNvv/3Ghg0bzjvmsWPHmDhxIvPnz8fVVY+OiYhcdEoQWD7ddIQ7PthA07q1WT6hNx0a+VZRccVtPZrBoHfXcjgtj0VjenBb1xBT6pCSK1NgiYqK4oYbbqBv3+JtxGNjYyksLCy2PCwsjNDQUNavX3/O8ex2OyNHjuSxxx6jXbt2ZSlJRETMZhg4JmP5p0Kbnee+3M6Updu4tWsI8x/oQaC3e9XW94cvNh/j1vfXE+TjwVcTehMRWufCK4npSn3T7aJFi4iLi2PTpk3/eC85ORk3Nzf8/PyKLQ8ODiY5OfmcY77yyiu4uLjw4IMPlrgOq9WK1Wo983VWVlaJ1xURkQpmGFCQDe7/fBz5VI6VqAVxxBxK58Wb2zOiR2MTCnQ0L3z1+93M/uUAQyMa8dLg9mpeeBEpVWBJTExk0qRJ/Pjjj3h4eFRIAbGxsbz11lvExcWVajbDadOm8fzzz1dIDSIiUk5FVnB2/8cstzuOZzI6Opb8QhvzH+hO92bmNC/MzCvkwUWb+XXvCZ65sS339Wqi5oUXmVJdEoqNjSU1NZWIiAhcXFxwcXFhzZo1vP3227i4uBAcHExBQQEZGRnF1ktJSaFevXpnHfPXX38lNTWV0NDQM2MePnyYRx55hCZNmpyzlqlTp5KZmXnmlZiYWJpdERGRilSUDy7FL/F8szWJW2atx6+2K8sn9jYtrOxLzeam99YSn5hB9H3dub+3Oi1fjEp1hqVPnz5s27at2LJ7772XsLAwpkyZQkhICK6urqxcuZKhQ4cCkJCQwJEjR4iMjDzrmCNHjvzHvTD9+/dn5MiR3Hvvveesxd3dHXd3c65/iojI/yjIgfws2PsTdrudZZuP8dXW40xsFsD9vZrifmIt5NeDeh2qtKyfdqbw0KfxNPDzYPmEXjQOUPPCi1WpAou3tzft27cvtszT05OAgIAzy++//34efvhh/P398fHxYeLEiURGRtKjR48z64SFhTFt2jQGDx5MQEAAAQHFU7erqyv16tWjdevWZd0vERGpSr6NwLcRWfmFTF4Uz6qEQh7vfwVjr2zmOJuRcwKyjlZZOYZh8N7P+3jtxz30axvMa7d1wstdc6VezCr8T++NN97AycmJoUOHYrVa6d+/PzNnziz2mYSEBDIzMyt60yIiYqIDJ3IYFR1DaraVj+++jKvDgv5605oF7lUz1X1eQRGPLd7KN9uSeKhvSx68pqWaF9YAFsMwDLOLqAhZWVn4+vqSmZmJj4/6P4iIVKXVCalMXLiZQG93PryrK80DvYp/4NR+x68BzSu1jsS0PEZFx3AkLY/Xb+vEde3Pfv+kVB8l/fmt82MiIlJmhmHwwS8HeOX73VzVOog37+iEj4c5k3/+tv8kUfPj8PZwZdn4XrSuZ07HZ6kcCiwiIlIm+YU2pizdypfxxxl/VXMe6dfatOaF0esP88LXO4lsFsC7d3bGr7b6AdU0CiwiIlJqxzNOM3puDPtSc3hnWGcGdjSnB5y1yMazX+zg05hE7u/dlKkDwnBRP6AaSYFFRERKZdOhNMbNi8XdxZklY3vSvmEJ+gGdTgf/ZhVaR2pWPmPnxbL9eBb/ubUjt3RpVKHjS/WiwCIiIiW2YOMRnlu+nc6hdZg1PIIArxLOh5WfAR5+FVbHlsQMxsyNxcDgszGRdAqpuLGlelJgERGRCyoosvPC1zuYt+EII3s05tmBbXEtzaUXA3CqmEs1S2OPMnXZNto18GH2iC4E+VRMqxip3hRYRETkvE7mWBk/P47NR9KZNqQDw7qFlmGU8s+gUWSzM/273fx37UFu7dKIFwe3x91FzQsvFQosIiJyTtuPZTI6OoYCm52Fo3rQtYl/6QexZoNb+abEz8grYOLCzfy2/xT/GtiWu3uqeeGlRoFFRETOavmW4zy+ZAstg7yZPbILDfxqlW2gnFTwCi5zHXtSshkVHUPW6ULm3teNni3qlnksuXgpsIiISDE2u8F/fkhg1ur93NypAdOHhuPhWs5LL2U8G7JiRzIPfxpPiH9t5t3fnRD/2uWrQy5aCiwiInJGVn4hkxZuZs2eEzx5fRijLm9WMZdeStkFxm43eGfVPt74aQ8D2tfjP7d2xFPNCy9p+tMXEREA9v/RvPBEtpWP77mMq1oHXXilSpBrLeKRz7bw/Y5kHrm2FROuaaH7VUSBRURE4OfdqTy4cDPBvh4sn9CbpnXLd5NsWR055WheeDQ9jw9GdqFfOzUvFAcFFhGRS5hhGMxas58ZKxLoExbEG7d3wruimxfmZ0Cdphf82Lp9J4laEIdfLVeWRfWiVbCaF8pfFFhERC5RpwtsPLZkC19vTWLiNS2Y3LcVThXdvNAwHNPyN4g4z0cM5qw7xEvf7qJn8wDeHRaBb21zOj5L9aXAIiJyCTqanseYubEcOJHLe3dGcEN4/crZUO4JqB1wzqeE8gttPP3FdpbEHmX0Fc14vH9rNS+Us1JgERG5xGw8cIpx8+Oo7ebM0nE9advAp/I2Zs0G97OPn5KVz5i5sexMyuKN2zsyuLOaF8q5KbCIiFxC5m44zPPLd3BZE3/eGx6Bv6db5W0s5wRkHAafhv94a/ORdMbMjcXJYmHJ2EjCG/lVXh1SIyiwiIhcAgqK7Dy3fAcLfz/CPT2b8NQNbUrXvLAsrFng1xgCmhdbvDgmkaeWbadDI19mjYggyFvNC+XCFFhERGq4E9lWxs2LZcvRDF4Z2oHbLytL88LyK7LZeenbXcxZd4g7Lgvh+ZvaqXmhlJgCi4hIDbb1aAZj5sZSZDdYNDqSLo3rmFJHem4BExbGsfFAGv++qR0jejTWZHBSKgosIiI11BebjzFl6VbC6nkze2RX6vmac+lld3IWo6JjyLXamHt/dyKbB5hSh1zcFFhERGoYm93g1e93M/uXAwzp3JCXh3Qof/PCMhVSyOqDOYz/Zi+NAzxZOKoHjeqoeaGUjQKLiEgNkplXyIOLNvPr3hM8fUMb7u/d1JRLL3a7waK1u3jl9wKuDm/JjFvCqe2mHzlSdvruERGpIfalZvPAJzGk5xXyyX3duLxloCl15FiLmPxpPJm7DxDV91pG9emg+1Wk3BRYRERqgJ92pvDQp/HU9/Xgy6heNDGpeeGhk7mMnhvD8Yx85l7bhM5Xtj/nLLcipaHAIiJyETMMg/d+3sdrP+7h2jbBvH57J7zczfmn/Zc9J5iwII4AL3e+GHsZLU5vBSdNsy8VQ4FFROQilVdQxGOLt/LNtiQm9WnJpD4tK755YQkYhsFHaw/y8re7uLxlIG8P64yvPQvslTjlv1xyFFhERC5CiWl5jIqO4UhaHu+PiOC69pXUvPAC8gttPPn5Nj7ffIyxVzbnsf6tcXayQFrWOXsIiZSFAouIyEVm/f5TjJ8fi5eHC5+P70lYPXOCQXJmPmPmxrA7OZu37ujETZ3+1jPIsOveFalQCiwiIhcJwzCIXn+YF77eSY9m/rw7LII6ldm88DxiD6czdl4srk4WloztSYdGvv/8kAKLVCAFFhGRi4C1yMazX+zg05hE7uvVlCevD8OlspsXnsOnm47wzBc76Bjiy6wRXajr5X72DxpG1RYmNZoCi4hINZealc/YebFsP5bFjFvCubVriCl1FNrsvPj1Tj5Zf5g7u4fyr4HtcHM5R2iyOIG9qGoLlBpNgUVEpBrbkuhoXmg3DD4d04POoeY0L0zLLWD8/FhiDqXz4s3tGdGj8flXcPeBjENVUptcGhRYRESqqc/jjvLE59toW9+H2SO7EOxjTvPCncezGD03htMFNhaM6kG3pv4XXsnZBWw6wyIVR4FFRKSaKbLZmf7dbv679iC3dGnEize3N6d5IfDN1iQeXbyFZoGefDomkoZ+tUq2opOLLglJhVJgERGpRjLyCpi4cDO/7T/FcwPbck/PJqY1L3zjpz28s2ofAzs24NWh4dRyK0VosjiDYau8AuWSU65bzKdPn47FYuGhhx46syw/P5+oqCgCAgLw8vJi6NChpKSknHOMwsJCpkyZQocOHfD09KRBgwbcddddHD9+vDyliYhcdPakZHPTe+vYdiyT6Pu6cW8vczotZ+cXMnpuDO/+vI8nBoTx9h2dShdWAJycwa7AIhWnzIFl06ZNzJ49m/Dw8GLLJ0+ezFdffcXixYtZs2YNx48fZ8iQIeccJy8vj7i4OJ555hni4uL4/PPPSUhIYNCgQWUtTUTkovPDjmQGv7cODxdnlkf1pleLuqbUcfBkLoNn/sbGg2l8fPdljL2yedlC06l9uiQkFapMl4RycnIYPnw4H374IS+++OKZ5ZmZmXz00UcsWLCAa665BoA5c+bQpk0bNmzYQI8ePf4xlq+vLz/++GOxZe+++y7dunXjyJEjhIaGlqVEEZGLgt1u8M6qfbzx0x6ua1eP127riKdJzQvX7DnBxAVx1PV254uoXjQP9Cr7YLZCqNeh4oqTS16ZzrBERUVxww030Ldv32LLY2NjKSwsLLY8LCyM0NBQ1q9fX+LxMzMzsVgs+Pn5laU8EZGLQq61iPHz43jjpz08fG0rZg6PMCWsGIbB7DX7uXfO73Rt4l/+sAJgzQaPs8x+K1JGpf6bsWjRIuLi4ti0adM/3ktOTsbNze0fQSM4OJjk5OQSjZ+fn8+UKVMYNmwYPj7n7o9htVqxWq1nvs7KyirZDoiIVANHTuUxem4MiWl5zB7Zhf7t6plSR36hjSlLt/Jl/HGirm7Ow9f+0bywvIpOg4s5j2FLzVSqwJKYmMikSZP48ccf8fCo+G/EwsJCbrvtNgzDYNasWef97LRp03j++ecrvAYRkcq2bt9JohbE4VvLlWVRvWgV7G1KHcczTjNmbix7U7N5Z1hnBnZsUDED222OmW7VS0gqUKkuCcXGxpKamkpERAQuLi64uLiwZs0a3n77bVxcXAgODqagoICMjIxi66WkpFCv3vn/9/BnWDl8+DA//vjjec+uAEydOpXMzMwzr8TExNLsiohIlTMMgznrDnLXx7/ToaEvX5oYVjYdSmPQu2tJyy1g6bieFRdWAApywdWz4sYToZRnWPr06cO2bduKLbv33nsJCwtjypQphISE4OrqysqVKxk6dCgACQkJHDlyhMjIyHOO+2dY2bt3Lz///DMBAQEXrMXd3R1393M03BIRqWbyC208/cV2lsQeZdTlTZlynXnNCxf+foRnv9xO59A6zBoeQcC5mheWVUEuuCmwSMUqVWDx9vamffv2xZZ5enoSEBBwZvn999/Pww8/jL+/Pz4+PkycOJHIyMhiTwiFhYUxbdo0Bg8eTGFhIbfccgtxcXF8/fXX2Gy2M/e7+Pv74+ZmTut0EZGKkpKVz5i5sexMyuL12zoyJKKRKXUU2uy88NVO5m44zF2RjXnmxra4VkZoKjoNriWcEVekhCr8dvQ33ngDJycnhg4ditVqpX///sycObPYZxISEsjMzATg2LFjLF++HIBOnToV+9zPP//MVVddVdEliohUmc1H0hkzNxYni4XFYyLpGOJnSh0nc6yMnx/H5iPpTBvSgWHdNGWEXFwshmEYZhdREbKysvD19SUzM/OC97+IiFSFxTGJPLVsO+0b+vD+yC4EeZvz1Mz2Y5mMmRuLtcjO+yMi6NqkBM0Ly+PUfsevAc0rdztSI5T057d6CYmIVLAim52Xvt3FnHWHuL1rCC/c3A53F3OaF3615TiPLdlCyyBvZo/sQoOSNi8UqWYUWEREKlB6bgETFsax4UAazw9qx12RjU3pB2SzG7z2QwIzV+/n5k4NmD403LSOzyIVQYFFRKSC7E7OYlR0DDn5Rcy7vzuRzS/8xGNlyMovZNLCzazZc4Inrw9j1OXNTAlNIhVJgUVEpAJ8vz2Jhz/bQqh/bRY80IMQ/9qm1LH/RA6jomM4mW1lzr3duLJVoCl1iFQ0BRYRkXKw2w3eXLmXt1fu5YYO9Zlxazi13cz5p/Xn3ak8uHAzwb4efDmhN03rmjQXisUCNeN5DqlGFFhERMoox1rE5E/j+WlXCo/1b834q5qbcunFMAzeX3OAV1fspk9YEG/c3glvD9cqr0OkMimwiIiUweFTuYyKjuF4Rj4fjuxK37bBptRxusDG40u38tWW4zx4TQse6tsKp4poXlgeOrsilUCBRUSklH7de4IJCzbj7+nGF1E9aRFkTj+gYxmnGR0dw4ETucwcHsH1HeqbUodIVVBgEREpIcMw+GjtQV7+dhe9Wwbyzh2d8a1tzqWXjQdOMX5+HLXcnFk6ridtG2jCTKnZFFhEREogv9DGk8u28XncMcZc0YzHrwvD2aRLL/M2HOZfy3dwWRN/3hsegb9nNeu5pptupRIosIiIXEByZj5j5sawOzmbN2/vxM2dG5pSR0GRnX99tYMFG49wT88mPHVDm8ppXlheCitSCRRYRETOI/ZwOmPnxeLiZGHJ2J50aOQLB9ZA7gmo5VeOkUt3dibjdCHvrNpL0olcPrmiCVe2SoaDyeXYfnn9GUosf/v9H1xrQ93WVV2Q1HAKLCIi5/DZpkSe/mI74Y18mTWiC4He7rBvJVizILgdBLWpkjq2Hc1k9OIYiuxteH9UF7o0rlMl2xWpThRYRET+R6HNzotf7+ST9YcZ1i2U5we1w81ic3QhPrkXGkdWWVj5Mv4Yjy/ZSlg9b2aP7Eo9X3M6PouYTYFFRORv0nILGD8/lphD6bx4c3tG9GjseOPkfrA4QcMukJMKe3/kzGWd2nWgQYTjZtMKYrMbvLpiN7PXHGBIRENeHtxBzQvlkqbAIiLyh53Hsxg9N4a8AhvzH+hO92Z/a15Yt6Xj14DmxVey5kDy1goNK5l5hTy4aDO/7j3BMze25b5eTdS8UC55CiwiIsA3W5N4dPEWmtb1ZNHoHjSqU8LmhfkZ4OFXYXXsS81mVHQsabkFfHJfNy5vqeaFIqDAIiKXOLvd4I2f9vDOqn3cGF6fGbd0pJZbKS69FFnBxb1Calm5K4VJi+Jp4OfB8gm9aBxgUvNCkWpIgUVELlnZ+YVM/jSelbtTefy61oy70rzmhTNX7+c/PyRwbZtgXr+9E17u+udZ5O/0N0JELkkHTzqaF6Zk5vPR3V25Jsyc5oV5BUU8tngr32xLYlKflkzq09L85oUi1ZACi4hcctbsOcHEBXHU9XLniwm9aB7oZUodiWl5jJ4by+FTubw/ogvXta9nSh0iFwMFFhG5ZBiGwYe/HmD6d7u5slUgb97RGd9a5WxeaNgh4zCkH/r7QsfkrxYoNhPsmWWwMymbmT/vwdstlM/H30BYPTUvFDkfBRYRuSTkF9p4YulWvog/zvirmvNIv9YV07ywbsu/HnkuAcMwmLvhMM9/t5ObQlvw4Y1t8VVYEbkgBRYRqfGOZ5xmzNxY9qZm8/awzgzq2MCUOqxFNp77cgeLNiVyX6+mPNndFZfq2LxQpBpSYBGRGi3mUBpj58Xi7uLMkrE9ad/Q15Q6UrPzGTcvjm1HM5lxSzi3dg1xTPUvIiWiwCIiNdbC34/w7Jfb6RxSh5kjIqjrVTHzpZTWlsQMxsyNxW4YfDqmB51D1bxQpLQUWESkxim02Xnhq53M3XCYET1CefbGdri5mHPpZdnmo0xZuo229X2YPaw9wW5WRy8iLFCYB64lnFFX5BKnwCIiNcrJHCvj58ex+Ug6Lw/uwJ3dQ02po8hm55Xvd/Phrwe5pUsjXry5PR6ZByA9A5xdAQOcXMFTU++LlIQCi4jUGNuPZTJmbizWIhsLRvXgsib+ptSRmVfIhIVx/Lb/FM8NbMs9Pf9oXmhxAs8A8G9mSl0iFzMFFhGpEb7acpzHlmyhRZAXH4yMpIFfLVPq2JOSzajoGDJPFzL3vm70bFG3+AcMw5S6RC52CiwiclGz2Q1e+yGBmav3c1OnBkwfEl665oUV6IcdyUz+NJ4Q/9rMva87oQG6P0WkoiiwiMhFKyu/kEkLN7N6zwmmDghj9BXNTGleaLcbvPvzPl7/cQ8D2tfjP7d2xFPNC0UqlP5GichF6dDhg7y/6HPcTxfxZb/mhBctgO9zHPeJGHbHpZeA5uDfvHwb+jP//G1a/TNfA/lFdj745QAxh9N4q0tDBnZ0wylx9T8+hwVwqQV1W5WvHpFLlAKLiFx0ft6dyoML9xDk04UPo7rS7GzNCw0DkuIhOxmcXMCnIbh7O351qphHnI+cymP03BgS05rwxvCb6ddOzQtFKosCi4hcNAzD4P01B3h1xW6uaR3Em3d0wtvjHM0LLRZo0PnPFSHrGFhz4MDPf5yBsYN3fQhoAW6lv9fkt30nGb8gDt9ariyL6kWrYO9y7JmIXIgCi4hcFE4X2Hh86Va+2nKcCVe34OFrW+FU0uaFFgv4NnL8Pijsr+UZiXBoLbh7QZ0m4HPhHkOGYfB/vx3ixW920bN5AO8M64xfbbfS75CIlIoCi4hUe8cyTjM6OoYDJ3J5784IbgivXzED+4U4XvmZkH4Ykrc5lnsFgXcD8A4u9nFrkY2nl21ncexRRl3elCnXhal5oUgVKdfftOnTp2OxWHjooYfOLMvPzycqKoqAgAC8vLwYOnQoKSkp5x3HMAyeffZZ6tevT61atejbty979+4tT2kiUkNsPHCKQe+sJSOvkKXjelZcWPk7D1+oHw6t+jte3g0g+zjs+QH2/gh7fyJjy7e8/O4sDmz5lQ9v8OWpKwNxseVrXhWRKlLmwLJp0yZmz55NeHh4seWTJ0/mq6++YvHixaxZs4bjx48zZMiQ84716quv8vbbb/P++++zceNGPD096d+/P/n5+WUtT0RqgHkbDjP8vxtpGezF8gm9aNvAp2o27B3suP+lVT9oeS2bXTsy4utsdud6M21Ie66tnw+HfoVNH8Km/0LOiaqpS+QSZjGM0v/3ICcnh4iICGbOnMmLL75Ip06dePPNN8nMzCQwMJAFCxZwyy23ALB7927atGnD+vXr6dGjxz/GMgyDBg0a8Mgjj/Doo48CkJmZSXBwMP/3f//HHXfcUaKasrKy8PX1JTMzEx+fKvpHTUQqRUGRnX99tYMFG49wd2Rjnr6xLa5Veekl9xRkJkLuSX7dd4JP1h3EO6gxTw/uQoCn219nVWrVcbxMmPtFpKYo6c/vMv0LEBUVxQ033EDfvn2LLY+NjaWwsLDY8rCwMEJDQ1m/fv1Zxzp48CDJycnF1vH19aV79+7nXEdEaq4T2VaG/3cDi2MSmT6kA8/f1L5qw8ofbDknWbDxEB/9eoBOrZoy/Y7uBDRo4egDFNDc8artr7AiUkVKfdPtokWLiIuLY9OmTf94Lzk5GTc3N/z8/IotDw4OJjk5+azj/bk8OLj4zW3nWwfAarVitVrPfJ2VlVXSXRCRamr7sUxGR8dQYDNYNLoHXRqb07wwHW8m/OLFhgMNeG5gX0Z29MGSdwoOrnE8Dg3gWRcCWjqeMBKRSleqwJKYmMikSZP48ccf8fDwqKyaSmTatGk8//zzptYgIhXny/hjvL3kJ64MyOPRvi0IsG2DA//zoXOdzXCp5Xhs2af8N+QmJDuaF+ZYi5h3f3cimwc43qjtD3Vb/vXB7BTHxHQFeY4Q49sI6rUv9/ZF5OxKFVhiY2NJTU0lIiLizDKbzcYvv/zCu+++y4oVKygoKCAjI6PYWZaUlBTq1Tv7DJB/Lk9JSaF+/frF1unUqdM5a5k6dSoPP/zwma+zsrIICQkpze6ISDVgsxu8umI3s9ccYHTbOjzSrzvugaWcTj/9MBTmlW6dglzIOg6nMyA/A4ANxwp5clUanv6hzH+gOyH+teHUfkjdCa5/dH/++1T74GgFYLGAs+ZiEalMpQosffr0Ydu2bcWW3XvvvYSFhTFlyhRCQkJwdXVl5cqVDB06FICEhASOHDlCZGTkWcds2rQp9erVY+XKlWcCSlZWFhs3bmTcuHHnrMXd3R13d/fSlC8iVeV4vGNmWee//R09y8mR3AI7M3/ey+5jmbzfI4T+7eph8Q8F53PMXnsubrXh+GZIO+C4VOPu4xgj9wR4+P31OVshZCc5fk0/CCHdIaA5do86vLVyL3NWbub2Vu48Enkaj1O/QRqOQONaG1r0PcfGRaQqlCqweHt707598VOenp6eBAQEnFl+//338/DDD+Pv74+Pjw8TJ04kMjKy2BNCYWFhTJs2jcGDB5+Zx+XFF1+kZcuWNG3alGeeeYYGDRpw8803l38PRaTqWbMcP+Bdzv2fin2p2YyKjuVUTgvevSeCK1oFln17Pg0cL7sd8k45tl+QVzysgCPYNO4FLn+dDcmxFvHwvFh+3JXCo/27MP6q5qZ0fBaR86vwmW7feOMNnJycGDp0KFarlf79+zNz5sxin0lISCAzM/PM148//ji5ubmMHj2ajIwMevfuzffff2/6fTIiUgaFpx2XSc4TVlbuSmHSonjq+3qwfEJvmtT1rJhtOzmBV6DjVQKHT+UyKjqG4xn5/PeurvRpE3zhlUTEFGWah6U60jwsItVE+iHHJZe/36D6B8MwmLl6P//5IYG+bYJ54/ZOeLmb0yFk7d6TRC2Iw9/TjQ/v6kKLIDUvFDFDSX9+q5eQiFQsww5Ozv9YnFdQxGNLtvLN1iQe7NOSh/q0LHnzwooszzD4aO1BXv52F5e3DOTtYZ3xrVXKe2ZEpMopsIhI6RXkQsoOxxM0eSehcU9o2MVxD8npdHApfjk3MS2P0XNjOXwql1nDIxjQoRL6AZVAfqGNJ5dt4/O4Y4y5shmP9w/D2YTQJCKlp8AiIqWXfsjx5EzbQZC6G/LSYd9Pjkd+6zSBOo3PfHTDgVOMnx+Hp7szn4/vSVg9cy7ZJmfmM2ZeLLuTsnjrjk7c1KmhKXWISNkosIjIhVmzISPRMW8JOG6oDWwNbp7QqMtZVzEMg7kbDvPCVzvp1tSf9+6MoI6nOXOVxB5OZ+y8WFycLCwZ25MOjXxNqUNEyk6BRUQu7M/5S1xrQXA7qOV33o9bi2w89+UOFm1K5N5eTXjq+ja4mNAPCOCzmESeXradjiG+zBzehUBvzd8kcjFSYBGRC6vt77hPJXkbZB49b2BJzc5n3Lw4th3N5NVbwrmtqzkzUBfa7Lz0zS7+77dD3Nk9lH8NbIebizmhSUTKT4FFRC4sPxN2fwN2m6Nb8e5vwcnFMVlbUFvH/CfAlsQMxsyNxW4YLBrTg4jQOqaUm5ZbQNT8ODYdSuPFm9szokfjC68kItWaAouIXJiHL3S6EwrzwVYAHj5gGHByr+Nm26LT/JAWyITvM2lT34cPRnYh2MeciR93JWUxKjqG0wU25j/Qne7NAkypQ0QqlgKLiJzf6XTIS/urU3JBnuOy0B9zrdgMmLstn3c3H2JgRDteGtweD9d/zsNSFb7dlsQjn22hWaAnn46JpKFfLVPqEJGKp8AiIsWl7oaMI47p9QHcvcAz0HFGBRxnW+o5eodl5hUyYWEcv+0v4qkb23Bvryam9OGx2w3e+GkP76zax8CODXh1aDi13MwJTSJSORRYRKQ4WwEYNnB2Ad8Qx8v1n5d39qZkMyo6hvS8Qj65txu9W9Y1oVjIzi9k8qdbWLk7hSnXhTH2ymZqXihSAymwiEhx9cMdL1shZCbCwTWOsysu7uAVDN71+OFgAZM/jadRndosn9CNxgEV1LywlA6edDQvTMnK5+O7L+PqsCBT6hCRyqfAIiJn5+zqeCLIv5nja1sR9qwkln23go9j0ujdtjuv39YJT5OaF67Zc4KJC+Ko6+3OF1G9aB7oZUodIlI1FFhEpERyi+DRb1L5fbvBK+1zuabrCZyyD4Fb879uyK0ChmHw4a8HmP7dbq5sFchbwzrj46HmhSI1nQKLiFxQYloeo6JjSEzL4/WR19C3XT1Ho8PkLXA8DhpEVEloyS+08cTSrXwRf5zxVzXnkX6t1bxQ5BKhwCIi5/XbvpOMXxCHj4crn4/vRes6Fsf8K1nHoKjA0U/Imu2Ym6USJWWeZnR0LHtTs3lnWGcGdmxQqdsTkepFgUVEzsowDD757RAvfbODISG5PNPbC6/sDZBfC7zrQ2ik40bcKhBzKI2x8+Jwd3FiydietG+o5oUilxoFFhFx+HOCuNPpFOSe4pPfjrB27wn+1a4et193DS7+jav0XpU/Lfz9CM9+uZ3OoXWYOTyCul5qXihyKVJgERGHrONwNIY0z2aMXelGfFIjpg0dwNAujUwpp9Bm599f7yR6/WFG9mjMswPb4mpSx2cRMZ8Ci4g4BLcj3lqf5+d+SwMjle+ub0Jz/wOQYXdMHleFZ1dO5VgZPz+OuCPpvDy4A3d2D62ybYtI9aTAIiIALIk9ypPLttGuQVOeG3ELQT4ejr5B6Qdh7w+ABeo0cczL4lx5/3TsOJ7J6OhYrEU2FozqwWVN/CttWyJy8VBgEbnEFdnsvPztbj5ed5Dbujbi3ze3x93ljz48brUhuJ3jZbfDsRjHzLct+lRKLV9vPc6ji7fQMsib2SO70EDNC0XkDwosIpew9NwCJiyMY8OBNJ4f1I67Ihufuw+PkxO4ef1xr0us4zFmi5NjCv+cFEf35jpNwbdhqeuw2Q1e+yGBmav3c1OnBrwyNNy0js8iUj0psIhcohKSHc0Ls/MLmXtfN3q2KEHzwuC2ULcVWLMgPxPsNsdZmNBIsBdCyk7H/Cz1OoBryc6OZOUX8tCieFYnpPLk9WGMulzNC0XknxRYRC5B329P5uHP4gn1r838B7oT4l+75Cs7u0Btf8erGDcIuQwyj8LhdeDf3HHPy3nCx4ETOTwQHcOJbCsf33MZV7VW80IROTs9IyhyCbHbDd78aQ9j58VyVetAlo7rWbqwUhK+jaDJ5Y7Zb/d8D6czzvqxnxNSuem9dThZLCyf0FthRUTOS2dYRC4ROdYiHv40nh92pvBov1ZEXd2i4i+9WLMh94TjvpbMRPBpALX8in3EMAxm/3KAV77fTZ+wIN64vRPeal4oIhegwCJyCTh8KpdR0TEcz8jnw7u6cm3b4IrdgK0QjsY47mPxbgAuHtD0CnD3Lvax0wU2pizdyvItx5l4TQsm922Fk5oXikgJKLCI1HBr954kakEcdWq7smx8T1oGe194pZIoyINDax0319b2h7QD0DjSMU/LWRzLOM3o6BgOnMjlvTsjuCG8fsXUISKXBAUWkRrKMAw+WnuQl7/dRe+WgbxzR2d8a1fgpRfD5rih9nSa47FmN09HiDmL3w+mMW5eLLXcnFk6ridtG1RuZ2cRqXkUWERqoPxCG08u28bncccYc0UzHr8uDOeKvvTi7g0tr3X8PmkLGHbH4847vgDX2uDhC3Wa8HncYZ5akUzHJoHMHN4Ff0+3iq1DRC4JCiwiNUxyZj5j5sWyOymLN2/vxM2dSz+RW6nVC4f0Q47HmBv3BKAgI4nPFy8kYf8+nm4Tzm133qjmhSJSZgosIjVI7OF0xs6LxcXJwuKxkYQ38quaDVss4N/0zJcnc6yMW3SQtEQfnu59BVc3MODASsdEc1lHIaS7Y3I5EZESUmARqSE+i0nk6WXb6dDIl1kjIgjy9jClju3HMhkdHUOBzWD26Jvp0viPCeb2/+yYyr9WHdj9LaTsgKZXgo9uvhWRC1NgEbnIFdrsvPTNLv7vt0MM6xbCvwa1+6t5YRX7Mv4YU5ZupXWwN++P7EJ9379Nz9/kcsdEcq6e0OEW8Ax09CMSESkBBRaRi1habgFR8+PYdCiNf9/cnhHdQ03pw2OzG8xYkcD7a/YzpHNDXh7S4Z/NC0/tdfxaqw4ENK/yGkXk4qbAInKR2pWUxajoGPIKbMx7oDs9mgWc+8Mn90H6wfP29SkV449fLZBrtTFrzT52Hc1kVo9QrmvnjuXQz2feP/PZg2scjz77NITQ7hVTh4hcMhRYRC5C325L4pHPttC0rieLRvegUZ2z9APKS4O0g5B3yjE9fqPL/jFNfnntS81hVHQMabkteffezlzeMvDcH27Zt0K3LSKXllI9Yzhr1izCw8Px8fHBx8eHyMhIvvvuuzPv79+/n8GDBxMYGIiPjw+33XYbKSkp5x3TZrPxzDPP0LRpU2rVqkXz5s3597//jWEY511P5FJktxu89kMC4+fHcU2bIJaMi/wrrNjtjtlmD6+HPSvg1D6o0xha9YOQbhUeVlbuSmHwe+twcbLwZVSv84cVEZFyKtUZlkaNGjF9+nRatmyJYRh88skn3HTTTWzevJkmTZrQr18/OnbsyKpVqwB45plnGDhwIBs2bMDJ6ezZ6JVXXmHWrFl88skntGvXjpiYGO699158fX158MEHy7+HIjVEdn4hkz/dwsrdKTzWvzXjr2ruuF+lIM8xcVtBDvg1huC2jknbKolhGMxcvZ///JBA3zbBvHF7J7zcdbJWRCqXxSjnqQx/f39mzJhBSEgIAwYMID09HR8fx53/mZmZ1KlThx9++IG+fc9+OvjGG28kODiYjz766MyyoUOHUqtWLebNm1fiOrKysvD19SUzM/PM9kVqioMnHc0LUzLzefu2tlxdv8gxs2zeKTidDg06g1dQpdeRV1DEY0u28s3WJB7s05KH+rRU80IRKZeS/vwu87STNpuNRYsWkZubS2RkJFarFYvFgru7+5nPeHh44OTkxNq1a885Ts+ePVm5ciV79uwBYMuWLaxdu5YBAwacd/tWq5WsrKxiL5GaaM2eE9z07lrsdoNlUb24uqknZBxxhJW6raBV/yoJK0fT87hl1np+3p3K+yMiePhadVoWkapT6vO427ZtIzIykvz8fLy8vFi2bBlt27YlMDAQT09PpkyZwssvv4xhGDzxxBPYbDaSkpLOOd4TTzxBVlYWYWFhODs7Y7PZeOmllxg+fPh565g2bRrPP/98acsXuWgYhsF/fz3ItO92cUWrQN66ozO+tf5oXhjSDY7Fwsk9EBhW6fOZbDhwivHz4/B0d+bz8T0Jq6ezmCJStUp9hqV169bEx8ezceNGxo0bx913383OnTsJDAxk8eLFfPXVV3h5eeHr60tGRgYRERHnvH8F4LPPPmP+/PksWLCAuLg4PvnkE/7zn//wySefnLeOqVOnkpmZeeaVmJhY2l0RqbbyC208/NkWXvp2F6OvaM5Hd1/2V1gBcK0FTXqDXygkxTtusk3ZAYWnK7QOwzCYu/4QI/67kbB63iyP6q2wIiKmKPc9LH379qV58+bMnj37zLKTJ0/i4uKCn58f9erV45FHHuGxxx476/ohISE88cQTREVFnVn24osvMm/ePHbv3l3iOnQPi9QUSZmnGR0dy97UbF4ZGs5NnUrQvNAwIPOo4ykha5Zjcrbgdo5fy6igyM5zy7ez8PdE7uvVlCevD8NFzQtFpIKV9Od3uW/tt9vtWK3WYsvq1q0LwKpVq0hNTWXQoEHnXD8vL+8fZ2CcnZ2x2+3lLU3kohNzKI2x8+Jwc7awZGxP2jcs4dM+Fgv4hThe25eCk4vjMecySs3OZ9y8OLYdzWTGLeHc2jWkzGOJiFSEUgWWqVOnMmDAAEJDQ8nOzmbBggWsXr2aFStWADBnzhzatGlDYGAg69evZ9KkSUyePJnWrVufGaNPnz4MHjyYCRMmADBw4EBeeuklQkNDadeuHZs3b+b111/nvvvuq8DdFKn+Fv5+hGe/3E7nkDrMHBFBXS/3C690Nh6+ENqjzHVsPZrB6OhY7IbBp2N60Dm07GdpREQqSqkCS2pqKnfddRdJSUn4+voSHh7OihUruPbaawFISEhg6tSppKWl0aRJE5566ikmT55cbIz9+/dz8uTJM1+/8847PPPMM4wfP57U1FQaNGjAmDFjePbZZytg90Sqv0KbnX9/vZPo9YcZ3j2U5wa2w83FnEsvyzYf5Yml22hT34fZI7sQ7GNOx2cRkf9V7ntYqgvdwyIXo1M5VsbPjyP2cDr/GtSOET0al3/QfT9Bi9JNg2+zG7zy/W4++OUAt3RpxIs3t/9n80IRkUpQZfewiEjZ7DieyejoWPILbSwY1YNuTf1NqSMzr5AJC+P4bf8pnhvYlnt6NjGl47OIyPkosIiY4Outx3l08RZaBHkxe2QkDf1qlW9Aw3BMzZ93CmxFJV5tb0o2o6JjyDhdSPR93ejVom756hARqSQKLCJVyG43eO3HBN77eT+DOjbglaHh1HIr5aWXrOOOLsz/O+eKuxfUDnA8zlwCP+5MYfKn8TT0q8XyqO6EBpyl47OISDWhwCJSRbLyC5m8KJ5VCalMHRDG6CuanfvSy/F4RzBxdiu+3AIUFUBgawhoXqY6DMPg3VX7eO3HPVzXrh6v3dYRTzUvFJFqTv9KiVSBAydyeCA6hhPZVj6+5zKubn2B3j+utR1nSupUwE24f5NrLeKxJVv4dlsyD1/biglXt1A/IBG5KCiwiFSynxNSeXDhZoK83fkyqhfNAr0uvJLFCQxbhdaRmJbHqOgYEtPymD2yC/3b1avQ8UVEKpMCi0glMQyD2b8c4JXvd3N16yDevKMTPh6uF14RHDPXVuCMA7/tO0nUgjh8armyLKoXrYK9K2xsEZGqoMAiUglOF9iYsnQry7ccJ+rq5jx8bWucS3vppQIeLTYMg09+O8S/v9lFz+YBvDOsM3613S68oohINaPAIlLBjmWcZnR0DAdO5PLunZ25MbxB2QYq5xkWa5GNZ77YzmcxR3mgd1OeGKDmhSJy8VJgEalAvx9MY9y8WDxcnVkyLpJ2DUrYvPB/2Qod97GUUWpWPmPmxbLjeBav39aRIRGNyjyWiEh1oMAiUkHmbzzMc1/uoEvjOswcHkFAWZsXAji7glG2bsvxiRmMmRsDwOIxkXQM8St7HSIi1YQCi0g5FRTZef6rHczfeIS7IhvzzI1tcS3vpReLBSj9GEtjjzJ12TbaN/Dh/RFdCFLzQhGpIRRYRMrhZI6VcfNiiU/MYPqQDtzRLbRiBi7l/StFNjvTvtvNR2sPcnvXEF64uR3uLmpeKCI1hwKLSBltP5bJ6OgYCmwGC0f1oGsTc5oXZuQVMGHBZtYfOMXzg9pxV2RjNS8UkRpHgUWkDL6MP8aUpVtpFezN7JFdqO9bzuaFZZSQ7GhemJ1fyNz7u9GzuZoXikjNpMAiUgo2u8GMFQm8v2Y/gzs3ZNqQDni4nufSS9oBR6PC0j6i7OQEgWHn/cj325N5+LN4Qv1rM/+B7oT4q3mhiNRcCiwiJZR5upBJizbzy54TPHV9Gx64vGnJLr3UaVLmRoVnY7cbvL1qL2/+tJcbOtRnxq3h1HbTX2URqdn0r5xICexLzWF0dAwnc6x8MqIdl7vvg00rwd0bPP92GeZ/T6S41rrgmZLSyLEW8chn8fywM4XH+rdm/FXNdb+KiFwSFFhELmDlrhQeWhRPsK8Hyyf0pol/LUi3QZ2mcHIvOLuBZ5BjojeLBbAUn1a/ll+F1HHklKN54bGM03w4sit92wZXyLgiIhcDBRaRczAMg5mr9/OfHxLoExbMG7d3xPvP5oV/XuLx8IOifMBwTPRmGH/8/o9fC3Ih/VC5Lwmt3XuSCQvjqFPbjS+ietIiSM0LReTSosAichZ5BUU8vmQrX29N4sFrWvBQ31Y4na15oZMzFOaB3fbPsyuGATkpENKjzHUYhsHH6w7x0jc76d0ykHfu6Ixv7RJ2fBYRqUEUWET+x9H0PEZHx3LwZC4zh0dwfYf6Z/9g7klI2QHuXuAVXPzsyp+hpV644/0yyC+08dSy7SyNO8qYK5rx+HVhpe/4LCJSQyiwiPzNhgOnGD8/jtpuznw+vidt6vuc+8NFVnBygdoB4FuxzQVTsvIZPTeW3UlZvHl7J27u3LBCxxcRudgosIjguPQyb8Nhnv9qJ5c18ee94RH4e7qdfyXfho77VtIPwcl9cObkx9/OghTlQ9gNpaol7kg6Y+fG4uxkYcnYnnRoVMaOzyIiNYgCi1zyCorsPLd8Owt/T+Senk146oY2JW9e6BfieP3pWBwc/g08fMDZHXzOcTnpHD6LSeTpZdsJb+TLrBFdCPQuR8dnEZEaRIFFar78TMfrjL/OgJzKLeTJZdvYmZTNO9e3ZmBHP8hNPutn/3pU+WzL/lxuQKOuYCuEvJMlnuG20GbnpW928X+/HWJYt1CeH9QON5dydnwWEalBFFik5stJhdMZjrMefwsQCSlZPL98B3bD4P1b29KuvifkZ/y1XrGwYZx72d+XW5zBxQlc3MHNE7yCLlheem4BUQvi+P1gGi/e3J4RPRqXdg9FRGo8BRap+SxOUNu/2FwoyzYf5YmlBwmr34rZI7pQz9fDlNJ2J2cxKjqGXKuN+Q90p3uzAFPqEBGp7hRY5NLwx6Ubm93gle9388EvBxga0YiXBrc/f/PCSvTdtiQeWbyFJgGeLBzVg0Z11LxQRORcFFjk0mAYZOYVMnHRZtbuPcEzN7blvl5NTOnDY7cbvPnTHt5etY8bw+sz45aO1HIzJzSJiFwsFFjkknDoVC73fLmW9LxCou/rTu+WdS+8UiXIzi9k8qdbWLk7hceva824K9W8UESkJBRYpMZbt+8UL367Cze/Jiyf0IvGAZ6m1HHoZC6jomNIzszno7u7ck2YmheKiJSUAovUWIZh8O6qfXy+ciu9WgTyxPBeeLmb8y3/y54TTFgQR10vd76Y0IvmgWWbrl9E5FKlwCI1Uq61iMeWbOHbbck816spd0c2wcmEsGIYBh+tPcjL3+7iylaBvHlHZ3xrqXmhiEhpKbBIjZOYlseo6BiOpOXx/oguXFc/15Q68gttTP18G8s2H2PcVc15tF9rNS8UESkjBRapUX7bd5KoBXF4e7iybHwvWtfzhlP7/2dG2sqXlHmaMXNj2ZOSzdvDOjOoY4Mq3b6ISE2jwCI1gmEYfPLbIf79zS4imwXw7p2d8av9R/PCvDSo06TKaok9nMaYuXG4uzixZGxP2jdU80IRkfIqVbOSWbNmER4ejo+PDz4+PkRGRvLdd9+deX///v0MHjyYwMBAfHx8uO2220hJSbnguMeOHWPEiBEEBARQq1YtOnToQExMTOn3Ri5J1iIbU5Zu5V9f7eSenk34v3sv+yusAFgzwSuwSmpZ9PsR7vhgA83qevLlhF4KKyIiFaRUgaVRo0ZMnz6d2NhYYmJiuOaaa7jpppvYsWMHubm59OvXD4vFwqpVq1i3bh0FBQUMHDgQu91+zjHT09Pp1asXrq6ufPfdd+zcuZPXXnuNOnXqlHvnpOZLzcrnjg828EX8cf5za0eeubEtLn/vtFyYD85u5x6gghTa7Dz75Xae+Hwbt18WwrwHulPXS52WRUQqisUwSthO9hz8/f2ZMWMGISEhDBgwgPT0dHx8fADIzMykTp06/PDDD/Tt2/es6z/xxBOsW7eOX3/9tTxlkJWVha+vL5mZmWe2LzVbfGIGY+bGYBgwe2QXOoeeJeRmHXdcEqrXvtLqOJVjJWpBHLGH03l+UHvu7B5aadsSEalpSvrzu8z96202G4sWLSI3N5fIyEisVisWiwV397/+V+nh4YGTkxNr16495zjLly+na9eu3HrrrQQFBdG5c2c+/PDDC27farWSlZVV7CWXjqWxR7lt9noa+NXiq4m9zx5WAApPg2utSqtjx/FMBr27jn2pOSwY1UNhRUSkkpQ6sGzbtg0vLy/c3d0ZO3Ysy5Yto23btvTo0QNPT0+mTJlCXl4eubm5PProo9hsNpKSks453oEDB5g1axYtW7ZkxYoVjBs3jgcffJBPPvnkvHVMmzYNX1/fM6+QkJDS7opchIpsdv799U4eWbyFmzo2YNHoHgT7mNNp+ZutSdwyaz11PF1ZPqE3lzXxN6UOEZFLQakvCRUUFHDkyBEyMzNZsmQJ//3vf1mzZg1t27blhx9+YNy4cRw8eBAnJyeGDRvGzp076datG7NmzTrreG5ubnTt2pXffvvtzLIHH3yQTZs2sX79+nPWYbVasVqtZ77OysoiJCREl4RqsIy8AiYs2Mz6A6d45oY23N2zBM0L0w6AYUBA8wqrw243eO3HBN77eT83dWrA9CHhal4oIlJGJb0kVOrHmt3c3GjRogUAXbp0YdOmTbz11lvMnj2bfv36sX//fk6ePImLiwt+fn7Uq1ePZs2anXO8+vXr07Zt22LL2rRpw9KlS89bh7u7e7HLT1KzJSRnMyo6hqz8Qube142eLUrYvLB8t2j9Q1Z+IZMXxbMqIZWpA8IYfUUzNS8UEakC5Z6HxW63FzvTAVC3ruOHyapVq0hNTWXQoEHnXL9Xr14kJCQUW7Znzx4aN25c3tKkhvh+ezIPfxZPqH9t5j/QnRD/2qbUceBEDqOiY0jNtjLnnsu4qnWQKXWIiFyKShVYpk6dyoABAwgNDSU7O5sFCxawevVqVqxYAcCcOXNo06YNgYGBrF+/nkmTJjF58mRat259Zow+ffowePBgJkyYAMDkyZPp2bMnL7/8Mrfddhu///47H3zwAR988EEF7qZcjOx2g3dW7eONn/YwoH09/nNrRzxNal64OiGViQs3E+TtzpdRvWim5oUiIlWqVP/6p6amctddd5GUlISvry/h4eGsWLGCa6+9FoCEhASmTp1KWloaTZo04amnnmLy5MnFxvjzktGfLrvsMpYtW8bUqVN54YUXaNq0KW+++SbDhw+vgN2Ti1WOtYhHPotnxY4UHr62FROuboGTCX14DMNg9i8HeOX73VzTOog37+iEt4eaF4qIVLVyz8NSXWgelprjyClH88Kj6Xm8cXsn+rWrV/bBTu13/FqGm27zCx0z6H4Zf5wJV7fg4WtbmRKaRERqskq76VakMq37o3mhby1XlkX1olWwtyl1HMs4zZi5MexPzeW9OyO4Iby+KXWIiIiDAotUC4Zh8PG6Q7z87S56Ng/gnWGdi/cDqkKbDqUxbl4s7i7OLB3Xk7YNdMZORMRsCixiuvxCG08t287SuKOMvqIZj/dvXbwfUBVasPEIzy3fTpfGdXjvzggC1A9IRKRaUGARU6Vk5TN6biy7krJ44/aODO7cyJQ6CorsPP/VDuZvPMLdkY15+sa2uJoUmkRE5J8UWMQ0cUfSGTs3FieLhcVjIukY4mdKHSdzrIyfF8fmxHSmD+nAHd3UD0hEpLpRYBFTfBaTyNPLttOhkS+zRkQQ5G1OP6DtxzIZHR1Dgc1g0egedGmsfkAiItWRAotUqSKbnZe+3cWcdYe447IQnr+pHe4u5vThWb7lOI8v2UKrYG9mj+xCfd/K6+osIiLlo8AiVSY9t4CoBXH8fjCNf9/UjhE9GpvSh8dmN/jPDwnMWr2fwZ0bMm1IBzxc1bxQRKQ6U2CRKrE7OYtR0THkWm3Mvb87kc0DSr5y2oG/fv/nPIclDToFueD6V++hrPxCJi3czJo9J3j6hjbc37upmheKiFwEFFik0n23LYlHFm+hcYAnCx7oUfrmhRlHwDek+LKSTtDs5gm+jieP9qXmMDo6hlO5BXxyXzcubxlYujpERMQ0CixSaex2gzd/2sPbq/ZxQ3h9ZtwSTm23MnzLGXao0wScyn7ZZtXuFCYtjKeerwdfRvWiSV3PMo8lIiJVT4FFKkV2fiGTP93Cyt0pPNa/NeOval62Sy92O1icS35G5X8YhsGsNfuZsSKBvm2CeeP2TniZ1PFZRETKTv9yS4U7dDKXUdExJGXm89+7utKnTXDZB7NYwN0L8jPAs26pVj1dYOOxJVv4emsSD/ZpyUN9Wqp5oYjIRUqBRSrUL3tOMGFBHAFe7nwR1ZMWQeVsXmixOM6ylPJy0NH0PEZHx3LoVC6zhkcwoIOaF4qIXMwUWKRCGIbBR2sP8vK3u7i8ZSBvD+uMby3XihncZgWXkk8st/HAKcbNj8PT3ZnPx/ckrJ6aF4qIXOwUWKTc8gttTP18G8s2H2PMlc14vH8YzhV56cVuc9zHcgGGYTBv4xGeX76Dbk39ee/OCOp4mtPxWUREKpYCi5RLUuZpxsyNJSE5m7fu6MRNnRpW/EYM2wUvCRUU2Xlu+Q4W/n6Ee3s14anr25jW8VlERCqeAouUWezhNMbMjcPV2cKSsT3p0Mi34jdizQFboeMsyzlCy4lsK+PmxbL1aCav3hLObV1Dzvo5ERG5eCmwSJks+v0Iz3y5nU4hfswc3oVAb/fK2ZC7l2OmWsN+1re3Hs1gzNxYbHaDRWN6EBFap3LqEBERUymwSKkU2uz8++udRK8/zJ3dQ/nXwHa4uVTypZciK7j+86bbLzYfY8rSrYTV9+GDkV0I9jGn47OIiFQ+BRYpsVM5VqIWxBFzKJ0Xb27PiB6NK3+jdjtgOC4LOTueOrLZDV75fjcf/HKAoRGNeGlwezUvFBGp4RRYpER2HM9kdHQs+YU25j/Qne7NStG8sDycnMDZDexF4OxKZl4hExdtZt2+kzx7Y1vu7dVEzQtFRC4BCixyQd9sTeLRxVtoFujJB3dF0tCvVtUWYC8E11rsS83mgU9iSM8r5JN7u9G7ZelmvhURkYuXAouck91u8PqPe3j3530M7NiAV4eGU8vNnEsvP+1M4aFP42noV4vlE7rROEDNC0VELiUKLHJWWfmFTF4Uz6qEVKZcF8bYK5uZcunFMAyWxyfxUKyVfm2Def22TniqeaGIyCVH//LLPxw4kcOo6BhSs618fPdlXB0WZEodeQVFPLZ4K9k7EnmoTw8mXtNCzQtFRC5RCixSzOqEVCYu3EygtztfRPWieaCXKXUkpuUxKjqGxLQ8PunTkq59WppSh4iIVA8KLGWRnQxOf2/sZ4Bh/PV7+OPrv/++BO+V5HMWy98+x7mXleS94nvAot+P8MEvB7ihWQBP3dgEb6cUOJVywXX/Odj/bu9c+3b2r+MTM3j5m53Uc3fh/dva0sTl7JPGiYjIpUOBpSxshZCd5Pghe+a+jj9+tVj+5/d/vHfWz/39vfOt/zdnCx/nCyQlCCvWIjuvrtjNT7tSGd49lPt7Nzt788ILjfVnvRan4l+fbZ/P8rUBLIk9yus/HaRrk4a8eHN7fGu5gVu7C+6DiIjUbAosZeEX4njVAMczTjN6QQz7Ul2YcccABnZsYEod1iIbz36xg09jTvJA7wieGBCm5oUiInKGAsslbNOhNMbNi8XdxZklY3vSvmElNC8sgdSsfMbOi2X78Sxeu7UjQ7s0MqUOERGpvhRYLlELNh7hueXb6Rxah1nDIwjwqqTmhRewJdHRvNDA4LMxkXQK8TOlDhERqd4UWC4xBUV2Xvh6B/M2HGFkj8Y8O7AtriZdelkae5Spy7bRvoEP74/oQpCaF4qIyDkosFxCTuZYGT8/js1H0pk2pAPDuoWaUkeRzc7073bz37UHua1rI/59c3vcXdS8UEREzk2B5RKx/Vgmo6NjKLDZWTiqB12b+JtSR0ZeARMXbua3/ad4flA77opsrOaFIiJyQQosl4DlW47z+JIttAzyZvbILjSo6uaFf9iTks2o6BiyThcy9/5u9Gyu5oUiIlIyCiw1mM1u8J8fEpi1ej83d2rA9KHheLiac+llxY5kHv40nhD/2sy7vzsh/rVNqUNERC5OpbrbctasWYSHh+Pj44OPjw+RkZF89913Z97fv38/gwcPJjAwEB8fH2677TZSUko+U+r06dOxWCw89NBDpSlLziIrv5AHPtnE7DX7efL6MN64vZMpYcVuN3jrp72MmRvLla0DWTqup8KKiIiUWqkCS6NGjZg+fTqxsbHExMRwzTXXcNNNN7Fjxw5yc3Pp168fFouFVatWsW7dOgoKChg4cCB2+4WnVt+0aROzZ88mPDy8zDsjDvtP5HDze+uIPZzOnHu7MfqK5qbcJ5JrLWL8/Dje+GkPj/ZrxXt3RqjTsoiIlInFMEowd/t5+Pv7M2PGDEJCQhgwYADp6en4+PgAkJmZSZ06dfjhhx/o27fvOcfIyckhIiKCmTNn8uKLL9KpUyfefPPNUtWRlZWFr68vmZmZZ7Z/Kfp5dyoPLtxMsK8HH97VlaZ1PU2p48gpR/PCYxmneeP2TlzbNtiUOkREpHor6c/vMk/AYbPZWLRoEbm5uURGRmK1WrFYLLi7/zUBmYeHB05OTqxdu/a8Y0VFRXHDDTecN9T8L6vVSlZWVrHXpcwwDGau3sd9n2yiezN/lo3vaVpYWbfvJIPeW4u1yMay8T0VVkREpNxKfX5+27ZtREZGkp+fj5eXF8uWLaNt27YEBgbi6enJlClTePnllzEMgyeeeAKbzUZSUtI5x1u0aBFxcXFs2rSpVHVMmzaN559/vrTl10inC2w8tmQLX29NYuI1LZjctxVOZ2teWMkMw2DOukO89O0uerWoyzt3dMa3tuuFVxQREbmAUp9had26NfHx8WzcuJFx48Zx9913s3PnTgIDA1m8eDFfffUVXl5e+Pr6kpGRQUREBE5OZ99MYmIikyZNYv78+Xh4lG6W06lTp5KZmXnmlZiYWNpdqRGOpucxdNZvrNyVyszhETzSr7UpYSW/0MZjS7bywtc7eaB3U+bcc5nCioiIVJhy38PSt29fmjdvzuzZs88sO3nyJC4uLvj5+VGvXj0eeeQRHnvssX+s+8UXXzB48GCcnf96esVms2GxWHBycsJqtRZ773wuxXtYNh44xbj5cdR2c+aDkV1p28Cc/U7JymfM3Fh2JWXxytBwbu7c0JQ6RETk4lPSn9/lfmTDbrdjtVqLLatb1zEh2KpVq0hNTWXQoEFnXbdPnz5s27at2LJ7772XsLAwpkyZUuKwcqkxDIN5G4/w/PIdXNbEn/eGR+Dv6WZKLZuPpDNmbizOThYWj40kvJGfKXWIiEjNVqrAMnXqVAYMGEBoaCjZ2dksWLCA1atXs2LFCgDmzJlDmzZtCAwMZP369UyaNInJkyfTunXrM2P06dOHwYMHM2HCBLy9vWnfvn2xbXh6ehIQEPCP5eJQUGTnueU7WPj7Ee7p2YSnbmhjWvPCxTGJPLVsOx0a+TJrRARB3mpeKCIilaNUgSU1NZW77rqLpKQkfH19CQ8PZ8WKFVx77bUAJCQkMHXqVNLS0mjSpAlPPfUUkydPLjbG/v37OXnyZMXtwSXkRLaVcfNi2XI0g1eGduD2y8xrXvjSt7uYs+4Qw7qF8K9B7dS8UEREKlW572GpLmr6PSxbj2YwZm4sRXaD90d0oUvjOqbUkZ5bQNSCOH4/mMZzg9oxonuomheKiEiZVdk9LFL5vth8jClLtxJWz5vZI7tSz9ecSy+7k7MYFR1DrtXGvAe606NZgCl1iIjIpUeBpRqz2Q1e/X43s385wJDODXl5SAfTmhd+vz2Jhz/bQpMATxaO6kGjOuoHJCIiVUeBpZrKzCvkwUWb+XXvCZ6+oQ33925qyqUXu93gzZV7eXvlXm4Ir8+MW8Kp7aZvGxERqVr6yVMN7UvN5oFPYkjPK+ST+7pxectAU+rIsRYx+dN4ftqVwmP9WzP+KnOaKIqIiCiwVDM/7UzhoU/jqe/rwZdRvWhiUj+gQydzGT03hqSMfD66uyvXhKkfkIiImEeBpZowDIP3ft7Haz/u4do2wbx+eye83M354/llzwkmLIijrpc7y6J60SLIy5Q6RERE/qTAUg3kFRTx2OKtfLMtiUl9WjKpT0vTmhd+tPYgL3+7iytaBfLWHZ3xraV+QCIiYj4FFpMlpuUxKjqGI2l5vD8iguva1zeljvxCG09+vo3PNx9j3FXNebRfa5xNCE0iIiJno8BiovX7TzF+fixeHi58Pr4nYfXMmfAuOTOfMXNjSEjJ5q07OnFTJzUvFBGR6kWBxQSGYRC9/jAvfL2THs38eXdYBHVMal4YezidsfNicXWysGRsT9o39DWlDhERkfNRYKli1iIbz36xg09jErmvV1OevD4MF5OaF3666QjPfLGDTiF+zBwRQV0vd1PqEBERuRAFliqUmpXP2HmxbD+WxYxbwrm1a4gpdRTa7Lz49U4+WX+Y4d1DeW5gO9xczAlNIiIiJaHAUkW2JDqaF9oNg0/H9KBzqDnNC9NyCxg/P5aYQ+m8NLg9w7s3NqUOERGR0lBgqQKfxx3lic+30ba+D7NHdiHYx5zmhTuPZzF6bgynC2wsGNWDbk39TalDRESktBRYKlGRzc7073bz37UHuaVLI168ub1pzQu/2ZrEo4u30DzIk0/HRNLQr5YpdYiIiJSFAkslycgrYOLCzfy2/xTPDWzLPT2bmNa88I2f9vDOqn0M6tiAV4aGU8vNnNAkIiJSVgoslWBPSjajomPIPF1I9H3d6NWiril1ZOcXMvnTeFbuTmXqgDBGX9FMzQtFROSipMBSwX7YkczkT+MJ8a/N3Pu6ExpQ25Q6Dp7MZVR0DClZ+Xx8z2Vc3TrIlDpEREQqggJLBbHbDd5ZtY83ftrDde3q8dptHfE0qXnhmj0nmLggjkBvd76M6kWzQDUvFBGRi5sCSwXItRbxyGdb+H5HMg9f24oJV7cwrXnhB78c4JXvd3NV6yDevKMTPh5qXigiIhc/BZZyOnLK0bzwaHoeH4zsQr929UypI7/QxpSlW/ky/jhRVzfn4WvVvFBERGoOBZZyWLfvJFEL4vCt5cqyqF60CvY2pY7jGacZMzeWfak5vHtnZ24Mb2BKHSIiIpVFgaUMDMNgzrpDvPTtLno2D+CdYZ3xq21O88JNh9IYNy8WdxdnloyLpF0DNS8UEZGaR4GllPILbTz9xXaWxB5l1OVNmXKdec0LF/5+hGe/3E5EaB1mDo8gQM0LRUSkhlJgKYWUrHzGzI1lZ1IWr9/WkSERjUypo6DIzgtf72DehiPcHdmYp29si6tJoUlERKQqKLCU0OYj6YyZG4uTxcLiMZF0DPEzpY6TOVbGz49j85F0pg/pwB3dQk2pQ0REpCopsJTAl/HHeGzxVto39OH9kV0I8janeeH2Y5mMmRuLtcjOwlE96NpEzQtFROTSoMByAVsSM5j8aTw3d2rItKEdcHcxpw/PV1uO89iSLbQK9mb2yC7U91XzQhERuXQosFzA9zuS8fd0Z8atHU2Z18RmN/jPDwnMWr2fwZ0bMm1IB9M6PouIiJhFgeUCmtX15FSulZ93p9K3bXCVbjvztKN54eqEVJ66vg0PXN5UzQtFROSSpMByAYM7N+THnSmMmhvD7V1DGHNlc5rW9azUbeYX2vhi8zHe/GkveQVFzLm3G1e2CqzUbYqIiFRnFsMwDLOLqAhZWVn4+vqSmZmJj49PhY5ttxtErz/EO6v2cSq3gIhQP/q2DSayWQBtG/iU+74WwzA4npnPpoNprNlzgp92ppBTUMT17evz5A1taOin+1VERKRmKunPbwWWUsgvtPH99mS+2ZbE2r0nOV1ow9XZQvNAL5oHetGoTi2CfTwI8HLDx8MVD1dn3FwsWCwWimwG1iIbudYi0nILOZFt5XjGaQ6dymVvag5puQUAhNXzpl/bYIZENKJJJZ/JERERMZsCSyUrtNnZfiyTbccySUjO5sCJXI5m5JGaZcVaZD/vuk4W8Pd0o4FfLUL8a9MyyIu29X2IaFyHupqtVkRELiEl/fmte1jKyNXZic6hdegcWqfYcsMwyCuwkZ1fRH6hjQKbHcMAZycL7i5OeHu44O3hqk7KIiIipaDAUsEsFgue7i54uuvQioiIVBQ1oBEREZFqr1SBZdasWYSHh+Pj44OPjw+RkZF89913Z97fv38/gwcPJjAwEB8fH2677TZSUlLOO+a0adO47LLL8Pb2JigoiJtvvpmEhISy7Y2IiIjUSKUKLI0aNWL69OnExsYSExPDNddcw0033cSOHTvIzc2lX79+WCwWVq1axbp16ygoKGDgwIHY7ee+CXXNmjVERUWxYcMGfvzxRwoLC+nXrx+5ubnl3jkRERGpGcr9lJC/vz8zZswgJCSEAQMGkJ6efuYu38zMTOrUqcMPP/xA3759SzTeiRMnCAoKYs2aNVxxxRUlrqOqnxISERGR8ivpz+8y38Nis9lYtGgRubm5REZGYrVasVgsuLv/9Viuh4cHTk5OrF27tsTjZmZmAo4gdD5Wq5WsrKxiLxEREamZSh1Ytm3bhpeXF+7u7owdO5Zly5bRtm1bevTogaenJ1OmTCEvL4/c3FweffRRbDYbSUlJJRrbbrfz0EMP0atXL9q3b3/ez06bNg1fX98zr5CQkNLuioiIiFwkSh1YWrduTXx8PBs3bmTcuHHcfffd7Ny5k8DAQBYvXsxXX32Fl5cXvr6+ZGRkEBERgZNTyTYTFRXF9u3bWbRo0QU/O3XqVDIzM8+8EhMTS7srIiIicpEo9WQhbm5utGjRAoAuXbqwadMm3nrrLWbPnk2/fv3Yv38/J0+exMXFBT8/P+rVq0ezZs0uOO6ECRP4+uuv+eWXX2jUqNEFP+/u7l7s8pOIiIjUXOWe3cxut2O1Wostq1u3LgCrVq0iNTWVQYMGnXN9wzCYOHEiy5YtY/Xq1TRt2rS8JYmIiEgNU6rAMnXqVAYMGEBoaCjZ2dksWLCA1atXs2LFCgDmzJlDmzZtCAwMZP369UyaNInJkyfTunXrM2P06dOHwYMHM2HCBMBxGWjBggV8+eWXeHt7k5ycDICvry+1aqlLsYiIiJQysKSmpnLXXXeRlJSEr68v4eHhrFixgmuvvRaAhIQEpk6dSlpaGk2aNOGpp55i8uTJxcb485LRn2bNmgXAVVddVexzc+bM4Z577inDLomIiEhNo27NIiIiYppKn4dFREREpKrUmJbCf54o0gRyIiIiF48/f25f6IJPjQks2dnZAJpATkRE5CKUnZ2Nr6/vOd+vMfew2O12jh8/jre3NxaLxexyzsjKyiIkJITExETdW1NGOoblo+NXPjp+5adjWD41/fgZhkF2djYNGjQ470SzNeYMi5OTU4kmnDOLj49PjfxGq0o6huWj41c+On7lp2NYPjX5+J3vzMqfdNOtiIiIVHsKLCIiIlLtKbBUMnd3d5577jn1PSoHHcPy0fErHx2/8tMxLB8dP4cac9OtiIiI1Fw6wyIiIiLVngKLiIiIVHsKLCIiIlLtKbCIiIhItafAUk5xcXFce+21+Pn5ERAQwOjRo8nJySn2GYvF8o/XokWLzjtuWloaw4cPx8fHBz8/P+6///5/jFtTlOQY/unUqVM0atQIi8VCRkZGhY17Maus47dnzx5uuukm6tati4+PD7179+bnn3+uhD0wX2Ucw9WrV5/1777FYmHTpk2VtCfmqKzvQYBvvvmG7t27U6tWLerUqcPNN99cscVXE5V1DJs0afKP77/p06dXwh5UPgWWcjh+/Dh9+/alRYsWbNy4ke+//54dO3Zwzz33/OOzc+bMISkp6czrQn/phg8fzo4dO/jxxx/5+uuv+eWXXxg9enTl7IiJSnMMAe6//37Cw8MrfNyLVWUdP4Abb7yRoqIiVq1aRWxsLB07duTGG28kOTm5AvfAfJV1DHv27Fns73xSUhIPPPAATZs2pWvXrhW8F+apzO/BpUuXMnLkSO699162bNnCunXruPPOOyuw+uqhMo8hwAsvvFDs+3DixIkVVHkVM6TMZs+ebQQFBRk2m+3Msq1btxqAsXfv3jPLAGPZsmUlHnfnzp0GYGzatOnMsu+++86wWCzGsWPHKqT26qKkx9AwDGPmzJnGlVdeaaxcudIAjPT09AoZ92JWWcfvxIkTBmD88ssvZ5ZlZWUZgPHjjz9W+H6YqbKO4f8qKCgwAgMDjRdeeKGiSq8WKuv4FRYWGg0bNjT++9//Vlbp1UZlfg82btzYeOONNyqh6qqnMyzlYLVacXNzK9asqVatWgCsXbu22GejoqKoW7cu3bp14+OPPz5vG+3169fj5+dX7H9hffv2xcnJiY0bN1bwXpirpMdw586dvPDCC0RHR5+3OVZpx73YVdbxCwgIoHXr1kRHR5Obm0tRURGzZ88mKCiILl26VPyOmKiyjuH/Wr58OadOneLee+8tf9HVSGUdv7i4OI4dO4aTkxOdO3emfv36DBgwgO3bt1f8Tpissr8Hp0+fTkBAAJ07d2bGjBkUFRVVXPFVSIGlHK655hqSk5OZMWMGBQUFpKen88QTTwCQlJR05nMvvPACn332GT/++CNDhw5l/PjxvPPOO+ccNzk5maCgoGLLXFxc8Pf3r3Gn40tyDK1WK8OGDWPGjBmEhoZW2Lg1QWUdP4vFwk8//cTmzZvx9vbGw8OD119/ne+//546depU2v6YobKO4f/66KOP6N+/f7Vu0loWlXX8Dhw4AMC//vUvnn76ab7++mvq1KnDVVddRVpaWuXsjEkq83vwwQcfZNGiRfz888+MGTOGl19+mccff7xS9qOyKbCcxRNPPHHOm+X+fO3evZt27drxySef8Nprr1G7dm3q1atH06ZNCQ4OLpZ+n3nmGXr16kXnzp2ZMmUKjz/+ODNmzDBxDytfRR7DqVOn0qZNG0aMGFHi7Zf0z6a6Mvv4GYZBVFQUQUFB/Prrr/z+++/cfPPNDBw48KIJfGYfw787evQoK1as4P7776/IXaxUZh8/u90OwFNPPcXQoUPp0qULc+bMwWKxsHjx4krZ54pm9jEEePjhh7nqqqsIDw9n7NixvPbaa7zzzjtYrdbK2OXKZfY1qeooNTXV2LVr13lfVqu12DrJyclGdna2kZOTYzg5ORmfffbZOcf/+uuvDcDIz88/6/sfffSR4efnV2xZYWGh4ezsbHz++efl38EqUJHHsGPHjoaTk5Ph7OxsODs7G05OTgZgODs7G88+++wFaynNn011Yfbx++mnnwwnJycjMzOz2PIWLVoY06ZNq5ydrmBmH8O/e+GFF4zAwECjoKCgUva1Mph9/FatWmUAxq+//lpsebdu3Ywnn3yycna6gpl9DM9m+/btBmDs3r27Qve1KriYF5Wqr8DAQAIDA0u1TnBwMAAff/wxHh4eXHvttef8bHx8PHXq1DlnI6vIyEgyMjKIjY09c7/AqlWrsNvtdO/evVR1maUij+HSpUs5ffr0mc9t2rSJ++67j19//ZXmzZuXedzqzOzjl5eXB/CPs1FOTk5n/udb3Zl9DP9kGAZz5szhrrvuwtXVtZR7YR6zj1+XLl1wd3cnISGB3r17A1BYWMihQ4do3LhxWXapypl9DM8mPj4eJyenf9x2cFEwOzFd7N555x0jNjbWSEhIMN59912jVq1axltvvXXm/eXLlxsffvihsW3bNmPv3r3GzJkzjdq1axdLxBs3bjRat25tHD169Myy6667zujcubOxceNGY+3atUbLli2NYcOGVem+VZULHcP/9fPPP//j7vizHcPSjnuxqozjd+LECSMgIMAYMmSIER8fbyQkJBiPPvqo4erqasTHx1f2LlW5yvoeNAzH2SrA2LVrV2WVb7rKOn6TJk0yGjZsaKxYscLYvXu3cf/99xtBQUFGWlpaZe6OKSrjGP7222/GG2+8YcTHxxv79+835s2bZwQGBhp33XVXZe9OpVBgKaeRI0ca/v7+hpubmxEeHm5ER0cXe/+7774zOnXqZHh5eRmenp5Gx44djffff7/Y42t/fuMdPHjwzLJTp04Zw4YNM7y8vAwfHx/j3nvvNbKzs6tqt6rUhY7h/zrbX9SzHcPSjnuxqqzjt2nTJqNfv36Gv7+/4e3tbfTo0cP49ttvK2kvzFVZx9AwDGPYsGFGz549K6Hq6qOyjl9BQYHxyCOPGEFBQYa3t7fRt29fY/v27ZW0F+aqjGMYGxtrdO/e3fD19TU8PDyMNm3aGC+//PI5b0eo7iyGcZ7na0VERESqger/uISIiIhc8hRYREREpNpTYBEREZFqT4FFREREqj0FFhEREan2FFhERESk2lNgERERkWpPgUVERESqPQUWERERqfYUWERERKTaU2ARERGRak+BRURERKq9/wec1Z1qCdVQpAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 2 out of 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    }
   ],
   "source": [
    "print(\"Now back to polygonal HD drawing prep ... optional squish\")\n",
    "print(\"for many states we move in outcroppings via clipPoly's before running the wedgePoly solver\")\n",
    "vtdCP = tractCP.copy()\n",
    "#CODE TO SQUISH GEOMETRIES FROM CLIP LINES INTO THE MAP\n",
    "print(\"adding code here to 'push in' state panhandles ...\")\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "#Adding in here trimming ops\n",
    "toSquishUnitsList = list()\n",
    "toSquishGeomsList = list()  #combined list of geoms we will squish (over all squish operations)\n",
    "toSquishCountiesList = list()\n",
    "squishedShapesList = list()   #unit shapes after squishing, list over all squish operations\n",
    "if nClips > 0:\n",
    "    clipPoints = ast.literal_eval(trimDF[\"clipPoints\"][DFrow])   #sets of four points\n",
    "    farPoints  = ast.literal_eval(trimDF[\"farPoints\"][DFrow])    #pairs of points\n",
    "    newFarPoints  = ast.literal_eval(trimDF[\"newFarPoints\"][DFrow])   #pairs\n",
    "    cPts = [Point(clipPoints[i][0],clipPoints[i][1]) for i in range(len(clipPoints)) ]\n",
    "    fPts = [Point(farPoints[i][0],farPoints[i][1]) for i in range(len(farPoints)) ]\n",
    "    nfPts = [Point(newFarPoints[i][0],newFarPoints[i][1]) for i in range(len(newFarPoints)) ]\n",
    "    \n",
    "    for clipNo in range(nClips):\n",
    "        print(\"performing squish no\",clipNo+1,\"for state\",STATE)\n",
    "        n0,n1,n2,n3 = int(4*clipNo), int(4*clipNo+1), int(4*clipNo+2), int(4*clipNo+3)\n",
    "        clipPoly = Polygon([cPts[n0],cPts[n1],cPts[n2],cPts[n3] ] )\n",
    "        cutLine = LineString([cPts[n0],cPts[n1]] )\n",
    "        farLine = LineString([fPts[int(2*clipNo)],fPts[int(2*clipNo+1)] ] )\n",
    "        newFarLine = LineString([nfPts[int(2*clipNo)],nfPts[int(2*clipNo+1)] ])\n",
    "        \n",
    "        toSquishCounties = list()\n",
    "        toSquishUnits = list()\n",
    "        for c in range(nCounties):\n",
    "            if clipPoly.intersects(countyGeom[c]):\n",
    "                toSquishCounties.append(c)\n",
    "                if clipPoly.contains(countyGeom[c]):\n",
    "                    toSquishUnits = toSquishUnits + countyTractList[c]\n",
    "                else:\n",
    "                    for t in countyTractList[c]:\n",
    "                        if clipPoly.contains(vtdCP[t]):\n",
    "                            toSquishUnits.append(t)\n",
    "        print(\"clipPoly\",clipNo,\"intersects\",toSquishCounties,\"counties and a total of\",len(toSquishUnits),\"units\")\n",
    "        toSquishGeomUnion = vtdGeom[toSquishUnits[0]]\n",
    "        toSquishGeoms = list()\n",
    "        for t in toSquishUnits:\n",
    "            toSquishGeomUnion = toSquishGeomUnion.union(vtdGeom[t])\n",
    "            toSquishGeoms.append(vtdGeom[t])\n",
    "        unclippedGeom = MAP.difference(toSquishGeomUnion)\n",
    "        altCutLine = toSquishGeomUnion.buffer(0.001).intersection(unclippedGeom)\n",
    "        print(\"Here is the original cutLine and an alternate based on cut shapes\")\n",
    "        #plotPoly(MAP,0.1)\n",
    "        plotPoly(cutLine.buffer(0.02))\n",
    "        plotPoly(altCutLine,0.1)\n",
    "        plt.show()\n",
    "        # could use altCutLine for a more accurate squish at the squish-no_squish boundary ...\n",
    "        #newShapes = squish(clippedGeomList, altCutLine, farLine, newFarLine)\n",
    "        squishedShapes = squish(toSquishGeoms, cutLine, farLine, newFarLine) #..but may distort results\n",
    "        toSquishUnitsList.append(toSquishUnits)\n",
    "        toSquishGeomsList.append(toSquishGeoms)\n",
    "        toSquishCountiesList.append(toSquishCounties)\n",
    "        squishedShapesList.append(squishedShapes)\n",
    "        for geo in toSquishGeoms:\n",
    "            plotPoly(geo,0.1)\n",
    "            plotPoly(geo.centroid.buffer(0.004),0.1)\n",
    "        for geo in squishedShapes:\n",
    "            plotPoly(geo)\n",
    "            plotPoly(geo.centroid.buffer(0.002),0.4)\n",
    "        print(\"These are your orig (faint) and squished shapes for clip no\",clipNo+1,\"out of\",nClips)\n",
    "        plt.show()\n",
    "        pause = input(\"enter 1 when ready\")    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8ff566ff-c60d-4a5e-9369-fccccb9635e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now apply the squish to all impacted vtds.  \"tractGeom\" will retain original vtd shapes, so we can reset if needed\n",
    "for i, vList in enumerate(toSquishUnitsList):\n",
    "    squishedShapes = squishedShapesList[i]\n",
    "    for j, v in enumerate(vList):\n",
    "        vtdGeom[v] = squishedShapes[j]\n",
    "for t in range(nTracts):  #optional full state visualization after squish\n",
    "    if t not in allCutVTDs and t not in skipList:\n",
    "        plotPoly(vtdGeom[t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "90ef362f-f65f-4c02-bc1c-746dde29c827",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to use squished shapes (e.g. for MD, MN), enter 0 for unclipped states 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on confirming HD center 0 is inside the map's convex hull\n",
      "working on confirming HD center 503 is inside the map's convex hull\n",
      "working on confirming HD center 1004 is inside the map's convex hull\n",
      "working on confirming HD center 1736 is inside the map's convex hull\n",
      "working on confirming HD center 2237 is inside the map's convex hull\n",
      "working on confirming HD center 2737 is inside the map's convex hull\n",
      "working on confirming HD center 3397 is inside the map's convex hull\n",
      "working on confirming HD center 4070 is inside the map's convex hull\n",
      "Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note the MAP convex hull.  Overwrite with your own polygon if desired.\n"
     ]
    }
   ],
   "source": [
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]  #remember, this is after any squish operation\n",
    "print(\"Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\")\n",
    "useSquish = int(input(\"enter 1 to use squished shapes (e.g. for MD, MN), enter 0 for unclipped states\"))\n",
    "if useSquish == 1:\n",
    "    convexMAP = hdCP[countyTractList[uncutCountyList[0]][0]].buffer(0.1) \n",
    "    for v in range(nTracts):\n",
    "        if v not in skipList and v not in allCutVTDs and v not in coreVTDs:  #new - skip VRA core\n",
    "            convexMAP = convexMAP.union(hdCP[v].buffer(0.1))\n",
    "else:  #build the map via simple union of counties not wholly in fully cut-out districts\n",
    "    convexMAP = countyGeom[uncutCountyList[0]]\n",
    "    for c in uncutCountyList:\n",
    "        convexMAP = convexMAP.union(countyGeom[c])\n",
    "    #convexMAP = MAP.centroid\n",
    "    #for c in range(nCounties):\n",
    "    #    if c not in allFusedCounties:\n",
    "    #        convexMAP = convexMAP.union(countyGeom[c])\n",
    "MAPhull = convexMAP.convex_hull.buffer(0.01*convexMAP.area**0.5)\n",
    "plotPoly(MAPhull)\n",
    "popHDlist = list()\n",
    "for t in range(nTracts):\n",
    "    if t not in allCutVTDs and t not in skipList + coreVTDs:  #keep low-pop tracts as VEST may have assigned voters to them\n",
    "        popHDlist.append(t)  #we won't draw polygonal HDs for the VRA core nor envelope, but the envelope can be drawn in\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on confirming HD center\",t,\"is inside the map's convex hull\")\n",
    "    if hdCP[t].disjoint(convexMAP.convex_hull):\n",
    "        plotPoly(hdCP[t].buffer(0.03))\n",
    "        hdCP[t] = nearest_points(convexMAP.convex_hull,hdCP[t])[0]\n",
    "        plotCenter(\"m\",hdCP[t])\n",
    "    else:\n",
    "        plotPoly(hdCP[t].buffer(0.01))\n",
    "plotPoly(convexMAP)\n",
    "plotPoly(convexMAP.convex_hull)\n",
    "plotPoly(MAPhull)\n",
    "for c in allFusedCounties:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "print(\"Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Note the MAP convex hull.  Overwrite with your own polygon if desired.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3aafb7d6-12f3-4988-ac1e-6646439cf522",
   "metadata": {},
   "outputs": [],
   "source": [
    "nHDs = nTracts  #need to run this if we start option 2 from a vest list, not a previously run HD poly list\n",
    "HDcountyNo = countyNo.copy()\n",
    "populatedTractList = popHDlist.copy()  #nomenclature equivalency.  this excludes VRA cores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "cb166345-08fb-42a2-ba60-b1f198f0eec0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\n",
      "working on tract-tract distances for unit 0 out of 4604 . Time = 0\n",
      "working on tract-tract distances for unit 401 out of 4604 . Time = 74\n",
      "working on tract-tract distances for unit 804 out of 4604 . Time = 140\n",
      "working on tract-tract distances for unit 1204 out of 4604 . Time = 198\n",
      "working on tract-tract distances for unit 1837 out of 4604 . Time = 248\n",
      "working on tract-tract distances for unit 2237 out of 4604 . Time = 291\n",
      "working on tract-tract distances for unit 2637 out of 4604 . Time = 325\n",
      "working on tract-tract distances for unit 3104 out of 4604 . Time = 351\n",
      "working on tract-tract distances for unit 3648 out of 4604 . Time = 369\n",
      "working on tract-tract distances for unit 4204 out of 4604 . Time = 380\n",
      "All done; total elapsed  383 seconds for MO with 8 districts to map\n"
     ]
    },
    {
     "data": {
      "image/png": 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PV2hoqFavXq24uDgtW7ZMktS/f3998sknWr58uRITE1uo6wAAwFS3dQxMeXm5JCkiIkKSVFhYqKtXryohIcHbpl+/furdu7cKCgokSQUFBRo4cKCioqK8bRITE+XxeHTy5Elvm+vXUdumdh11qayslMfj8ZkAAEDr1OwAU1NTo9mzZ2vUqFEaMGCAJKmkpEShoaHq2rWrT9uoqCiVlJR421wfXmqX1y5rqI3H49Hly5frrCcjI0Ph4eHeqVevXs3tGgAACHDNDjBut1ufffaZNm3a1JL1NFtaWprKy8u9U3Fxsd0lAQCAO6RJx8DUmjlzpnbu3KkDBw6oZ8+e3vnR0dGqqqrShQsXfEZhSktLFR0d7W1z5MgRn/XVnqV0fZsbz1wqLS2V0+lUhw4d6qzJ4XDI4XA0pzsAAMAwTRqBsSxLM2fO1LZt25SXl6e4uDif5UOHDlX79u2Vm5vrnXfmzBmdO3dOLpdLkuRyuXTixAmVlZV52+Tk5MjpdCo+Pt7b5vp11LapXQcAAGjbmjQC43a7tXHjRr3//vvq0qWL95iV8PBwdejQQeHh4Zo6dapSU1MVEREhp9OpF198US6XSyNHjpQkjR8/XvHx8XrmmWe0dOlSlZSUaMGCBXK73d4RlOnTp+uNN97QvHnzNGXKFOXl5WnLli3KzuZCXwAAoIkjMKtWrVJ5eblGjx6tHj16eKfNmzd72yxfvlwTJ07UpEmT9Mgjjyg6Olp//vOfvcuDg4O1c+dOBQcHy+Vy6emnn9azzz6rxYsXe9vExcUpOztbOTk5Gjx4sJYtW6a1a9dyCjUAAJDUxBEYy7Ju2SYsLEyZmZnKzMyst01sbKx27drV4HpGjx6tTz/9tCnlAQCANoJ7IQFNdLpff7tLAIA2jwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMICNMqfn2V0CABiJAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEmDYqPT3d7hIAAGg2Agxu6XS//naXAACADwIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDCAn0TvK7K7BABoNQgwAADAOAQYAABgHAIMgJsM3DDQ7hIAoEEEGBjty/kf210CAMAGBBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgGmDOMMEzZGbd7f359P9+ttYCQAQYAAAgIEIMACa5PqRmPpkTs/z/lx7CwVupQCgJRFgTJcebncFAAD4HQEGwB0Rva/IZyRG0k3PAaC5CDAAAMA4BBhTsevo1thGAYORFwAtjQAToPrMz7a7BAAAAhYBBkCdGnO2EQDYhQATwJYlT/T+XDsiw8gMAAAEmIBUV3CpbzkAAG0RAQZAq/Dl/I/tLgGAHxFgYCT+swKAto0AAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMgBYVva/I7hIAtAEEGAAAYBwCDAAAMA4Bpo1JT0+3uwQAAG4bAQYAABiHAAMAAIxDgAEAAMYhwAB+kDk9z9b35+7dAFobAgyAgLEseaLdJQAwBAEGgF/VXuguel+RMqfnqc/8bC1Lnqg+87O9bQgyAG6FAAMAAIzT5ABz4MABPfroo4qJiVFQUJC2b9/us9yyLC1cuFA9evRQhw4dlJCQoM8//9ynzTfffKPJkyfL6XSqa9eumjp1qi5duuTT5q9//asefvhhhYWFqVevXlq6dGnTewcAAFqlJgeYiooKDR48WJmZmXUuX7p0qVauXKnVq1fr8OHD6tSpkxITE3XlyhVvm8mTJ+vkyZPKycnRzp07deDAAb3wwgve5R6PR+PHj1dsbKwKCwv1+9//Xunp6VqzZk0zuggAAFqbkKa+YMKECZowYUKdyyzL0muvvaYFCxbosccekyT98Y9/VFRUlLZv366nnnpKp0+f1u7du3X06FENGzZMkvT666/rZz/7mf7whz8oJiZG7733nqqqqvTOO+8oNDRU9913n4qKivTqq6/6BB0AANA2tegxMGfPnlVJSYkSEhK888LDwzVixAgVFBRIkgoKCtS1a1dveJGkhIQEtWvXTocPH/a2eeSRRxQaGuptk5iYqDNnzujbb7+t870rKyvl8Xh8JgAA0Dq1aIApKSmRJEVFRfnMj4qK8i4rKSlRZGSkz/KQkBBFRET4tKlrHde/x40yMjIUHh7unXr16nX7HQIAAAGp1ZyFlJaWpvLycu9UXFxsd0kAAOAOadEAEx0dLUkqLS31mV9aWupdFh0drbKyMp/l165d0zfffOPTpq51XP8eN3I4HHI6nT4TAABonVo0wMTFxSk6Olq5ubneeR6PR4cPH5bL5ZIkuVwuXbhwQYWFhd42eXl5qqmp0YgRI7xtDhw4oKtXr3rb5OTk6N5771W3bt1asmQAAGCgJgeYS5cuqaioSEVFRZK+O3C3qKhI586dU1BQkGbPnq3//u//1gcffKATJ07o2WefVUxMjB5//HFJUv/+/fXTn/5Uzz//vI4cOaK//OUvmjlzpp566inFxMRIkn71q18pNDRUU6dO1cmTJ7V582atWLFCqampLdZxAC3ndL/+dpcAoI1p8mnUx44d05gxY7zPa0NFSkqKsrKyNG/ePFVUVOiFF17QhQsX9NBDD2n37t0KCwvzvua9997TzJkzNW7cOLVr106TJk3SypUrvcvDw8O1d+9eud1uDR06VHfddZcWLlzIKdQAAEBSMwLM6NGjZVlWvcuDgoK0ePFiLV68uN42ERER2rhxY4PvM2jQIH38sZl30M2cnif36rF2lwGgCdLT05Wenm53GQAaqdWchQQAANoOAgwAADAOAcZm0fuKvD8vS56oPvOz7SumFfpyvpm7IdG28T0A3BoBxkaZ0/O8j3Z8YQ3cMNDv7wkAQEsgwNjk+pEXfyGwAABaCwIMGo1rfaAuuXl3210CgDaIAAMAAIxDgAEAAMYhwAAAAOMQYIAAsix5ot0lNIjjoAAECgIMODsJAGAcAgwAADAOAQYAABiHAIM2jbsPA4CZCDAAAMA4BBgAAGAcAgzajOvPtmLXEQCYjQCDVunL+R/bXUKdau9AbgdOlwfQmhBgAACAcULsLgBoimXJE/Vfm3faXUarlp6eLsXZXQWA6/WZn60Xz67Sf/X/WF9e2ameYRPrefzPC9LDvfPTNUf/E/c/mnR2UsOPmiTpuzvMx/yfUJ1/s+p/HxV60/z+//e0fRtEjMCgjbh+lxK7UgDAfAQYAABgHAIMjNFnfrbdJQAAAgQBBgAAGIcAgzZv4IaBPteFaeljZKL3FTX4vDGWJU9smWIAoJUgwMA2dl4TpT61Qeb6QHO6X3+fx5bSnCADAPgOAQZGaKkRiKaOtOTm3e3zCAAIDAQYAABgHAIMUI/WcL2YQL2lAgDcLgLMbWjpYyIQ+NiVBACBgQADBJhbXe/Gn9fDIaQDCFQEGMBU6eH1LmLXEYDWjgAD3EG3c6o4Vx4GgPoRYGC+BkYiTHer08dvHGlh5AVAW0GAgS3awkXcWrqPDY3IfDn/41YZ5LgCMYD6EGDQIM66sR+7kgDgZgQYmKsVjjjcil0jEpyNBCDQEGAAAIBxCDCQ5HuPIOO1gZEZDtYF0NYRYAAAgHEIMAAaZPSB3G1gNA5oqwgwgA1u5wJ3AAACDFqI0X+lAwCMQ4CBceq6LgoHtQYGRpYA+AsBBo3SUiMsbeEKvACAO48A40et6a/T2wk0rWk7AADsQYDxg+v/ww7kEYiBGwY2+LwuNwaZ3Ly7b+pv5vS8gO43Wjd2LwKtEwHGBiaPQOTm3e29rPyNj9cjsAAA7iQCDHzcySvymhzcAACBhQCD1o+LmQFAq0OAQcCr67RpAEDbRoBphrqO+QAAAP5DgLlDOIgVAIA7hwADIKA1dxdiY06fbsylAgAEJgLMbaq9Dgr3AgJan7p2Fzf0b54z7QD/IcAAaD3Sw/1+4bqW+uNlWfLEZr2OC/WhrSLAAMAt3DgSU9fFHBmFBfyLAAOg1as91sXEY14aNTJTx7WOGJlBa0eAaQF2n1bNFxXQcu7k1ajr0txdR/Xh+wBtBQGmhZk2jOzvL2vALo35rF8/UsMB+kBgI8A0U11fanaPxACAv/B9B7sRYPyEC9sBZgv0kZi2vuuorfe/LSLAAMAdYMsfLTbfuJQ/1OBPBBgACEAtfXBvoOGif7hdBBgAaG1sHokB/CGgA0xmZqb69OmjsLAwjRgxQkeOHLG7JAAAEAACNsBs3rxZqampWrRokY4fP67BgwcrMTFRZWVldpcGAABsFrAB5tVXX9Xzzz+v5557TvHx8Vq9erU6duyod955x+7SANQhoM7SaSW7UJp7J26gLQixu4C6VFVVqbCwUGlpad557dq1U0JCggoKCup8TWVlpSorK73Py8vLJUkej6fF67tUXa2Kipp6Hy9XVaimItT73rXPG3ysvKIrV6+qpvL/3fTo8Xh8Hq9cvSpPpSV5PFKlpYuVFY3qZ/XlalVWVt7ysXZd1Zcb7ueNjx6P56b+11RcarDfjam7rm1yUcHyBP2n70E3bIPKG+b/57Ex/b5xfn39bVTdt+j7jdugrn7W9+jTf4/npu1Q12P15cbVfau+37gN6vrs3+rR57Nxw2ff4/H4PNZ+9m+lrt95Xb/72nVlZGSoOvZ/nzfmd1/7GW/o377391lxqVF139jnuj4LN60no6eU9uUt++1Jc3rbtbS6/h00ts+SGv3vv7Ea+z1oquu/+xv8ndfxWKlbf+835nuvOd+DzVG7XsuyGm5oBaCvvvrKkmQdPHjQZ/7cuXOt4cOH1/maRYsWWZKYmJiYmJiYWsFUXFzcYFYIyBGY5khLS1Nqaqr3eU1Njb755ht1795dQUFBzV6vx+NRr169VFxcLKfT2RKlGontwDaoxXb4DtuBbVCL7fCdltoOlmXp4sWLiomJabBdQAaYu+66S8HBwSotLfWZX1paqujo6Dpf43A45HA4fOZ17dq1xWpyOp1t+oNZi+3ANqjFdvgO24FtUIvt8J2W2A7h4eG3bBOQB/GGhoZq6NChys3N9c6rqalRbm6uXC6XjZUBAIBAEJAjMJKUmpqqlJQUDRs2TMOHD9drr72miooKPffcc3aXBgAAbBawASY5OVn/+te/tHDhQpWUlOj+++/X7t27FRUV5dc6HA6HFi1adNPuqbaG7cA2qMV2+A7bgW1Qi+3wHX9vhyDLutV5SgAAAIElII+BAQAAaAgBBgAAGIcAAwAAjEOAAQAAxiHANCAzM1N9+vRRWFiYRowYoSNHjthdkt8dOHBAjz76qGJiYhQUFKTt27fbXZLfZWRk6MEHH1SXLl0UGRmpxx9/XGfOnLG7LL9btWqVBg0a5L1Ilcvl0ocffmh3WbZasmSJgoKCNHv2bLtL8av09HQFBQX5TP369bO7LFt89dVXevrpp9W9e3d16NBBAwcO1LFjx+wuy6/69Olz0+chKChIbrf7jr4vAaYemzdvVmpqqhYtWqTjx49r8ODBSkxMVFlZmd2l+VVFRYUGDx6szMxMu0uxTX5+vtxutw4dOqScnBxdvXpV48ePV0VFhd2l+VXPnj21ZMkSFRYW6tixYxo7dqwee+wxnTx50u7SbHH06FG99dZbGjRokN2l2OK+++7T119/7Z0++eQTu0vyu2+//VajRo1S+/bt9eGHH+rUqVNatmyZunXrZndpfnX06FGfz0JOTo4k6cknn7yzb9wyt19sfYYPH2653W7v8+rqaismJsbKyMiwsSp7SbK2bdtmdxm2KysrsyRZ+fn5dpdiu27dullr1661uwy/u3jxonXPPfdYOTk51o9//GNr1qxZdpfkV4sWLbIGDx5sdxm2e+mll6yHHnrI7jICzqxZs6y7777bqqmpuaPvwwhMHaqqqlRYWKiEhATvvHbt2ikhIUEFBQU2VoZAUF5eLkmKiIiwuRL7VFdXa9OmTaqoqGiTt/dwu91KSkry+Y5oaz7//HPFxMToBz/4gSZPnqxz587ZXZLfffDBBxo2bJiefPJJRUZG6oEHHtDbb79td1m2qqqq0rvvvqspU6bc1o2UG4MAU4d///vfqq6uvumqv1FRUSopKbGpKgSCmpoazZ49W6NGjdKAAQPsLsfvTpw4oc6dO8vhcGj69Onatm2b4uPj7S7LrzZt2qTjx48rIyPD7lJsM2LECGVlZWn37t1atWqVzp49q4cfflgXL160uzS/+sc//qFVq1bpnnvu0Z49ezRjxgz95je/0YYNG+wuzTbbt2/XhQsX9Otf//qOv1fA3koACERut1ufffZZm9zfL0n33nuvioqKVF5erj/96U9KSUlRfn5+mwkxxcXFmjVrlnJychQWFmZ3ObaZMGGC9+dBgwZpxIgRio2N1ZYtWzR16lQbK/OvmpoaDRs2TK+88ook6YEHHtBnn32m1atXKyUlxebq7LFu3TpNmDBBMTExd/y9GIGpw1133aXg4GCVlpb6zC8tLVV0dLRNVcFuM2fO1M6dO7Vv3z717NnT7nJsERoaqr59+2ro0KHKyMjQ4MGDtWLFCrvL8pvCwkKVlZVpyJAhCgkJUUhIiPLz87Vy5UqFhISourra7hJt0bVrV/3whz/UF198YXcpftWjR4+bwnv//v3b5O40SfrnP/+pjz76SNOmTfPL+xFg6hAaGqqhQ4cqNzfXO6+mpka5ubltcn9/W2dZlmbOnKlt27YpLy9PcXFxdpcUMGpqalRZWWl3GX4zbtw4nThxQkVFRd5p2LBhmjx5soqKihQcHGx3iba4dOmS/v73v6tHjx52l+JXo0aNuumSCn/7298UGxtrU0X2Wr9+vSIjI5WUlOSX92MXUj1SU1OVkpKiYcOGafjw4XrttddUUVGh5557zu7S/OrSpUs+f1WdPXtWRUVFioiIUO/evW2szH/cbrc2btyo999/X126dPEeBxUeHq4OHTrYXJ3/pKWlacKECerdu7cuXryojRs3av/+/dqzZ4/dpflNly5dbjr2qVOnTurevXubOibqt7/9rR599FHFxsbq/PnzWrRokYKDg/XLX/7S7tL8as6cOfrRj36kV155Rb/4xS905MgRrVmzRmvWrLG7NL+rqanR+vXrlZKSopAQP0WLO3qOk+Fef/11q3fv3lZoaKg1fPhw69ChQ3aX5Hf79u2zJN00paSk2F2a39TVf0nW+vXr7S7Nr6ZMmWLFxsZaoaGh1ve+9z1r3Lhx1t69e+0uy3Zt8TTq5ORkq0ePHlZoaKj1/e9/30pOTra++OILu8uyxY4dO6wBAwZYDofD6tevn7VmzRq7S7LFnj17LEnWmTNn/PaeQZZlWf6JSgAAAC2DY2AAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMM7/B9UvWEOUmqKYAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "our maxD was 6.1418198690657055\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 ....... ##########  THIS IS FOR TRACT - TRACT, despite the \"uu\" nomenclature\n",
    "print(\"Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\")\n",
    "#NOTE: FOR LARGE STATES, RESTRICT THE SEARCH TO COUNTIES WITHIN A 3/SQRT(nDistrict) DIAMETER OF THE HOME UNIT\n",
    "uuDist = [[int(maxD+1) for t in range(nHDs)] for t in range(nHDs)] #default: too big to capture\n",
    "closeCountyList = [list() for c in range(nCounties)]\n",
    "closeCountyDist = maxD   #min(maxD,3./float(nDistricts)**0.5 * maxD )  #use above maxD for these counties as well\n",
    "xScaleSquared = xScale*xScale\n",
    "if nDistricts < 10: #closeCountyDist >= maxD:  #small state\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]  #all counties are close enough\n",
    "else:\n",
    "    for c in uncutCountyList:\n",
    "        closeCountyList[c].append(c)\n",
    "        for cc in range(c+1,nCounties):\n",
    "            if cc in uncutCountyList:\n",
    "                if cc in neighborCountyList[c]:\n",
    "                    closeCountyList[c].append(cc)\n",
    "                    closeCountyList[cc].append(c)\n",
    "                else:    \n",
    "                    dist = getLongDist(countyCP[c], countyCP[cc],xScale)\n",
    "                    if dist < closeCountyDist:\n",
    "                        closeCountyList[c].append(cc)\n",
    "                        closeCountyList[cc].append(c)\n",
    "startTime = time.time()\n",
    "\n",
    "for i,t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on tract-tract distances for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime))\n",
    "    uuDist[t][t] == 0.\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "                dist = getLongDist(hdCP[t], hdCP[tt],xScale)\n",
    "                uuDist[t][tt], uuDist[tt][t] = dist, dist\n",
    "print(\"All done; total elapsed \",int(time.time()-startTime),\"seconds for\",STATE,\"with\",nDistricts,\"districts to map\" )\n",
    "plt.hist(uuDist)\n",
    "plt.show()\n",
    "print(\"our maxD was\",maxD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "fa855500-50e0-4090-9b5b-c2fe9e88803b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similar to above, but for angles\n",
      "working on unit-unit angles for unit 0 out of 4604 . Time = 0\n",
      "working on unit-unit angles for unit 401 out of 4604 . Time = 37\n",
      "working on unit-unit angles for unit 804 out of 4604 . Time = 71\n",
      "working on unit-unit angles for unit 1204 out of 4604 . Time = 102\n",
      "working on unit-unit angles for unit 1837 out of 4604 . Time = 127\n",
      "working on unit-unit angles for unit 2237 out of 4604 . Time = 151\n",
      "working on unit-unit angles for unit 2637 out of 4604 . Time = 168\n",
      "working on unit-unit angles for unit 3104 out of 4604 . Time = 182\n",
      "working on unit-unit angles for unit 3648 out of 4604 . Time = 192\n",
      "working on unit-unit angles for unit 4204 out of 4604 . Time = 197\n",
      "All done with angles; total elapsed seconds = 199\n"
     ]
    }
   ],
   "source": [
    "print(\"similar to above, but for angles\")  #convention is angle[a][b] is from a to b\n",
    "uuAngle = [[0. for t in range(nHDs)] for t in range(nHDs)]\n",
    "\n",
    "pi = 3.141592653\n",
    "twoPi = pi*2.\n",
    "startTime = time.time()\n",
    "for i, t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on unit-unit angles for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime)  )\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "            angLE = math.atan2(hdCP[tt].y - hdCP[t].y, xScale * (hdCP[tt].x - hdCP[t].x) )\n",
    "            uuAngle[t][tt], uuAngle[tt][t] = angLE % twoPi, (angLE + pi) % twoPi\n",
    "print(\"All done with angles; total elapsed seconds =\",int(time.time()-startTime) )\n",
    "#plt.hist(uuAngle)\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "cb457261-b939-4540-b533-c0c36c9ec22b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "769364.125 8 6154913.0 8.0 6154913.0\n",
      "6154913.0 5544921 0.90089\n"
     ]
    }
   ],
   "source": [
    "print(r3(aDP), nDistricts, statePop, statePop/aDP, trueStatePop)\n",
    "HDweight = [0 for t in range(nHDs)]\n",
    "for t in populatedTractList:\n",
    "    HDweight[t] = tractPop[t] / trueStatePop #skipping the cutList tracts\n",
    "print(statePop,np.sum([tractPop[t] for t in populatedTractList]), r5(np.sum(HDweight))) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ebb089fc-91b0-4b45-8e8e-3d0488c871bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\n"
     ]
    }
   ],
   "source": [
    "print(\"RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\")\n",
    "opt2nbrCtyList = [neighborCountyList[c].copy() for c in range(nCounties)]\n",
    "for i in range(nClips):\n",
    "    cList = toSquishCountiesList[i]\n",
    "    for c in cList:\n",
    "        for cc in cList:\n",
    "            for ccc in neighborCountyList[cc]:\n",
    "                if ccc not in opt2nbrCtyList[c] and ccc != c:\n",
    "                    opt2nbrCtyList[c].append(ccc)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "d3a99de2-bb42-42ab-9148-4b9a09a4540b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4604 4604 4604 0\n"
     ]
    }
   ],
   "source": [
    "#rerunning below to look for polytractlists being off\n",
    "print(len(populatedTractList),len(popHDlist),nTracts, np.min(tractPop))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "79c74a37-0607-4540-b855-39c562b6848e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\n",
      "For each Home District, we will consider a wedge as one-from-full when it is within 1069.49 of targetWedgePop\n",
      "I am working on HD number 0 of 4604 HDs.  Elapsed sec = 0\n",
      "I am working on HD number 401 of 4604 HDs.  Elapsed sec = 113\n",
      "I am working on HD number 804 of 4604 HDs.  Elapsed sec = 231\n",
      "I am working on HD number 1204 of 4604 HDs.  Elapsed sec = 335\n",
      "I am working on HD number 1837 of 4604 HDs.  Elapsed sec = 433\n",
      "I am working on HD number 2237 of 4604 HDs.  Elapsed sec = 537\n",
      "I am working on HD number 2637 of 4604 HDs.  Elapsed sec = 657\n",
      "I am working on HD number 3165 of 4604 HDs.  Elapsed sec = 788\n",
      "I am working on HD number 3895 of 4604 HDs.  Elapsed sec = 914\n",
      "I am working on HD number 4495 of 4604 HDs.  Elapsed sec = 1027\n",
      "1054.188 seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\n",
      "vtd avg and sd usage are 0.87503 0.32251\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 .......\n",
    "# BELOW modified Dec23 to use inter-unit distances and angles, (counties still wedgeIntersxn) otherwise similar to HD2\n",
    "# --THIS ESSENTIALLY TAKES THE ORIGINAL TRACT-BASED HD centerpoints, and redraws HD2 districts after convexifying corners and convex_hull\n",
    "print(\"Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\") \n",
    "#this is a hybrid of HD2 and the organic code, in that all wedge tracts must be in a chain of neighboring counties\n",
    "#General sequence: draw 4 equi-angle wedges with random starting orientation.  If not all can fill a quarter aDP ...\n",
    "# ... find the closest map boundary point to the tract center point in the shortest wedge.  Orient the 0th wedge to face this point\n",
    "# ... determine the \"maxWedgePop\" for this short wedge and the other three wedges extended past the boundary\n",
    "# ...  if this results in only one short wedge, or opposing short wedges, adjust wedge angles\n",
    "# Regardless of whether we re-oriented or adjusted angles, compute each wedgePop for infinite radius\n",
    "#   ... then adjust other targetWedgePops if some found to be short.\n",
    "#   ... for non-shorted wedges, use bisection method to adjust radius to meet targetWedgePop\n",
    "#   ... once total HDpop within tolerance, add/subtract a tract fraction to fulfill HDpop\n",
    "#  create a list of fully used tracts per HD, save the tract# of the split tract and its fractional use\n",
    "#  Compute tractUse across all HDs at the end from the tractUsageLists.  Defer patching and partisan calcs to another code\n",
    "\n",
    "pi=3.1415926536\n",
    "#MAPhull = MAP.convex_hull #used for exitAngle calc.  Defined in an above block to allow user modification\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2.*pi / nWedges\n",
    "angle, angle2, wedgePoly = [0.]*nWedges, [0.]*nWedges, [dummyPoly]*nWedges  #start and stop angle of each wedge\n",
    "pt1, pt2, pt3 = [Point(0,0)]*nWedges, [Point(0,0)]*nWedges, [Point(0,0)]*nWedges #these four define the polygon wedge for a growing home district\n",
    "tractUse = [0.] * nHDs  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "HDtractList = [list()]*nHDs\n",
    "splitTractNo = [-999]*nHDs  #the tract that is only partially used to finish each HD\n",
    "splitTractUse = [0.]*nHDs  #and this is what fraction of the split tract is included\n",
    "HDvPop = [0.]*nHDs\n",
    "#HDweight = [tractPop[t] / (statePop - excludedPop) for t in range(nTracts)]  #relative weight of each drawn HD\n",
    "HDPoly1 = [dummyPoly]*nHDs  #final 4-wedge shape, unionized from blockgroups / tracts\n",
    "HDarea = [0.]*nHDs  #geographical area of each home district (after boundary trim)\n",
    "HDradius = [[0.]*nWedges for t in range(nHDs)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nHDs)] #final starting angle for each HD wedge\n",
    "angle0 = [-999.] * nHDs  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "avgTractPop = statePop/len(populatedTractList)\n",
    "tolerPops = [0.8 * avgTractPop, 0.5 * np.max(tractPop)]  #threshold gap before adding one more unit to a wedge \n",
    "tolerPop = tolerPops[0]\n",
    "print(\"For each Home District, we will consider a wedge as one-from-full when it is within\",r3(tolerPops[0]),\"of targetWedgePop\")\n",
    "tractPrintInterval = 400  #for tracking progress\n",
    "levelL = 0.36 #sqrt(pop) for angle=std  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "maxAngleRatio = 1.9  #for tightening tract weighting near boundaries  #HD2\n",
    "maxAngle = 1.8*pi/2. # limit to avoid wedges too close to half a pie\n",
    "minAdjRatio = 0.5  #min ratio of pop of adjacent wedge (to min wedge) to targetWedgePop to not consider this a corner HD\n",
    "maxUncap = 0.5 #the max ratio of uncaptured pop in a maxWedge vs. target wedge pop that we will not stretch to include (7/23)\n",
    "oppWt = 0.0    #the fraction of gap between normal targetWedgePop and the minWedgePop that we allow the opposite wedge to add to tgtPop = minWedgePop\n",
    "maxWedgePop = [0.] * nWedges  #wedge pop if we explode wedge to maximum radius\n",
    "printDebug = \"no\"\n",
    "codeStartTime = time.time()\n",
    "hdCPpop = [HDweight[t] * statePop for t in range(nHDs)]\n",
    "countyHDlist = [list() for c in range(nCounties)]\n",
    "HDsToDraw = set(populatedTractList).difference(set(envelopeVs+coreVTDs+skipList))\n",
    "availVTDs = list(HDsToDraw)+envelopeVs\n",
    "for t in availVTDs: #excluding VRAcore and skipList; originally populatedTractList:\n",
    "    countyHDlist[HDcountyNo[t]].append(t)\n",
    "for kkkj, t in enumerate(HDsToDraw ):  #range(nTracts) : #loop on each tract. \n",
    "    hC = HDcountyNo[t]     #this tract's home county\n",
    "    HDtractList[t] = [t] #seed the list of tracts in this HD\n",
    "    wedgeList = [list() for w in range(nWedges)]   #list of each wedge's tracts, excluding home tract\n",
    "    barredList = list()  #list of wedge numbers for which we are barred from altering their targetWedgePops\n",
    "    if (kkkj % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on HD number {0} of {1} HDs.  Elapsed sec = {2}\".format(t,nHDs,int(time.time()-codeStartTime) ) )  \n",
    "    nActiveWedges = nWedges #active wedges have not run over boundary\n",
    "    wedgePop = [0.]*nWedges\n",
    "    targetWedgePop = [aDP / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    \n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to the midangle of our starting wedge\n",
    "    wedgeAngle = [avgWedgeAngle for w in range(nWedges) ] #reset to equi-angle when starting each tract\n",
    "    for nW in range(nWedges-1):\n",
    "        wedgeAngle[nW] += random.uniform(-0.0001,0.0001)  #this wiggle solves a later indexing ambiguity for corner tracts\n",
    "    wedgeAngle[nWedges-1] = 2.*pi - (np.sum(wedgeAngle) - wedgeAngle[nWedges-1] ) #squaring up to 2pi total\n",
    "    startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "    for nW in range(1,nWedges):\n",
    "        startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "    endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "    #  TRIAL LOOP TO SEE WHICH WEDGES CAN FILL TO TARGET POP w/equiangle wedges\n",
    "    maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]    \n",
    "    maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "    willFill = [0] * nWedges #would this wedge meet its target with infinite radius?\n",
    "    for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "        iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "        #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList) \n",
    "        nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "        maxWedgePop[nW] += (iCP + nonCP)\n",
    "        wedgeList[nW] = Li + Ln\n",
    "        if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "            willFill[nW] = 1\n",
    "     \n",
    "    if np.sum(willFill) < nWedges:  #at least one wedge couldn't reach its wedgePop target (went over boundary) ...\n",
    "        minW = maxWedgePop.index(np.min(maxWedgePop)) #.. so we will orient the 0th wedge to face the shortest wedgePop's closest boundary\n",
    "        exitAngle = getExitAngle(hdCP[t],maxWedgePoly[minW], MAPhull, startAngle[minW], endAngle[minW])\n",
    "        angle0[t] = exitAngle - 0.5*(2.*pi / nWedges)  #Now reset all angles based on new starting orientation.  All wedge angles still equal\n",
    "        startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "        for nW in range(1,nWedges):\n",
    "            startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "        endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "        maxWedgePoly = [buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]\n",
    "        \n",
    "        willFill = [0]*nWedges\n",
    "        #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation (wedge angles still constant)\n",
    "        maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop        \n",
    "        for nW in range(nWedges):   #... then add in-county and nonCounty wedge Pop from contiguous chain of counties\n",
    "            iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "            #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "            nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                    opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "            maxWedgePop[nW] += (iCP + nonCP)\n",
    "            wedgeList[nW] = Li + Ln\n",
    "            if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                willFill[nW] = 1       \n",
    "    \n",
    "    if np.sum(willFill) < nWedges:  #check if we need to modify wedge angles after possible re-orientation.  \n",
    "        # If so, re-draw maxWedgePoly's, re-calc maxWedgePops\n",
    "        nUnfilledWedges = nWedges - np.sum(willFill)\n",
    "        isChange, newInclA = getNewAngles(maxWedgePop, targetWedgePop, aDP, levelL, minAdjRatio, maxAngle, maxAngleRatio, nUnfilledWedges )\n",
    "        if isChange: #no longer equi-angle\n",
    "            newStartAngle = [0.5*(startAngle[nW]+endAngle[nW]) - 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            newEndAngle =   [0.5*(startAngle[nW]+endAngle[nW]) + 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            startAngle, endAngle, wedgeAngle = newStartAngle.copy(), newEndAngle.copy(), newInclA.copy()\n",
    "            maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], \n",
    "                                        maxD/math.cos(0.5*wedgeAngle[nW]), xScale ) for nW in range(nWedges) ]\n",
    "            willFill = [0]*nWedges\n",
    "            #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation and new wedge angles\n",
    "            maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "            for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "                iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])                \n",
    "                #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "                nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                        opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "                maxWedgePop[nW] += (iCP + nonCP)\n",
    "                wedgeList[nW] = Li + Ln\n",
    "            minW = wedgeAngle.index(np.max(wedgeAngle)) #should be 0th wedge, but playing it safe.  This is the 1st wide-angle wedge ..\n",
    "            oppW = int(int(minW+nWedges/2)%nWedges)   #and its opposite\n",
    "            if maxWedgePop[minW] > maxWedgePop[oppW] and maxWedgePop[oppW] < aDP / nWedges:  #minW and oppW are flipped after inclA adjmt\n",
    "                oppW = minW\n",
    "                minW = int(int(minW+nWedges/2)%nWedges)\n",
    "            if maxWedgePop[minW] < targetWedgePop[oppW]:  #we need to constrain oppW in this HD2 implementation; redistribute tgt to adjacents\n",
    "                maxNonOppW = np.sum(maxWedgePop) - maxWedgePop[oppW] #...but only if other wedges can pick up slack; need to check\n",
    "                minOppWedgePop = aDP - maxNonOppW  #cannot set oppW target below this or we won't reach aDP across all wedges\n",
    "                barredList = [oppW]\n",
    "                targetWedgePop[oppW] = max(minOppWedgePop, maxWedgePop[minW] + oppWt * (targetWedgePop[oppW] - maxWedgePop[minW]) )\n",
    "                tWPgap = aDP / float(nWedges) - targetWedgePop[oppW] \n",
    "                for nW in range(nWedges):\n",
    "                    if nW != minW and nW != oppW:\n",
    "                        targetWedgePop[nW] += tWPgap/float(nWedges - 2.)  #if oppW target is limited, allot to adjacent wedges\n",
    "            for nW in range(nWedges):\n",
    "                if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                    willFill[nW] = 1  \n",
    "    \n",
    "    if abs(np.sum(targetWedgePop) / aDP - 1.) > 0.001:\n",
    "        raise Exception(\"FAIL! Our target wedgepops\",targetWedgePop, np.sum(targetWedgePop),\"no longer add up to\",aDP)\n",
    "    \n",
    "    if np.sum(willFill) == nWedges:  #all wedges will fill.  Will any leave a small near-boundary remnant?  If so, pick up smallest remnant\n",
    "        remnantWedgePopFrac = [ ( maxWedgePop[w] - targetWedgePop[w] )/targetWedgePop[w] for w in range(nWedges) ]\n",
    "        if np.min(remnantWedgePopFrac) < maxUncap :  #lessen tWP's of *adjacent* wedges, then increase this wedge's target --> max\n",
    "            minW = remnantWedgePopFrac.index(np.min(remnantWedgePopFrac))\n",
    "            oppW = int((minW+nWedges/2)%nWedges)\n",
    "            #print(\"filling to boundary for tract,wedge, tWP, mWP =\",t,minW, r3(targetWedgePop[minW]), maxWedgePop[minW])\n",
    "            for nW in range(nWedges):\n",
    "                if nW != minW and nW != oppW:\n",
    "                    targetWedgePop[nW] -= (remnantWedgePopFrac[minW] * targetWedgePop[minW] ) / (nWedges - 2.)\n",
    "            targetWedgePop[minW] = maxWedgePop[minW]\n",
    "            #       OK, READY TO SOLVE FOR NON-FILLED WEDGE SIZES once we adjust targets for unfilled wedges\n",
    "    #print(t,\" prior to rebalanceTWP call, mWPs, tWPs are\",maxWedgePop, targetWedgePop)\n",
    "    targetWedgePop, willFill = rebalanceTWPs(maxWedgePop, targetWedgePop, barredList)\n",
    "    #if np.max(targetWedgePop) - np.min(targetWedgePop) > 0.02 * aDP: #debug\n",
    "    #    print(\"for tract\",t,\",  After rebalancing but before tweaks for blocky pop adds: willFill, targetWedgePops and maxWedgePops are ...\")\n",
    "    #    for w in range(nWedges):\n",
    "    #        print(w, willFill[w],r3(targetWedgePop[w]),int(maxWedgePop[w]) )\n",
    "    for w in range(nWedges):  #WHEW!  WE CAN FINALLY ASSIGN ALL WEDGES' POPS AND TRACTLISTS\n",
    "        loop = 0\n",
    "        if willFill[w] == 0:  #wedge is maxed out\n",
    "            wedgePop[w] = maxWedgePop[w]\n",
    "            #wedgeList[w] = ...  #we already captured this list = maxWedge list\n",
    "            HDradius[t][w] = maxD/math.cos(0.5*wedgeAngle[w])\n",
    "        else:  #need to solve for wedge radius to meet targetPop.  Use bisection as scipy minimize no faster\n",
    "            HDcpWP = hdCPpop[t] * wedgeAngle[w]/(2.*pi)\n",
    "            nonHDcpTWP = targetWedgePop[w] - HDcpWP\n",
    "            #wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeB(nontractTWP,t,hC,maxWedgePoly[w],tolerPop,tractCP, tractPop,\n",
    "            #                                                        countyNo,countyTractList,countyGeom, neighborCountyList,uuDist[t])\n",
    "            wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeC(nonHDcpTWP,t,hC, maxWedgePoly[w],startAngle[w], endAngle[w], tolerPop,\n",
    "                                                                    hdCP, hdCPpop,HDcountyNo, countyHDlist,countyGeom,\n",
    "                                                                    opt2nbrCtyList,uuDist[t],uuAngle[t])\n",
    "            popGap = nonHDcpTWP - wedgePop[w]  #gap between target and solved wedge pop; can be negative\n",
    "            notYetAdjusted, nextW = True, w+1  #looking to adjust a later wedge's target pop to minimize drift in total HD pop\n",
    "            while notYetAdjusted and nextW < nWedges:\n",
    "                if willFill[nextW] == 1 and maxWedgePop[nextW] > targetWedgePop[nextW] + popGap :  #can accommodate\n",
    "                    targetWedgePop[nextW] += popGap\n",
    "                    notYetAdjusted = False\n",
    "                nextW +=1          \n",
    "\n",
    "        HDangle[t][w] = startAngle[w]\n",
    "    #print(t,\"tract. After TWP adjustment, targetWedgePops are\",targetWedgePop)\n",
    "    HDtractList[t] = [t]\n",
    "    totPop = hdCPpop[t]\n",
    "    for nW in range(nWedges):\n",
    "        for tt in wedgeList[nW]:\n",
    "            HDtractList[t].append(tt)  #building the list of tracts in the Home District  (we'll keep up with below changes)\n",
    "            totPop += hdCPpop[tt]\n",
    "    offsetPop = totPop - aDP  #we have solved for all wedge radii to get each within one tractPop of target ... \n",
    "    HDvPop[t] = totPop\n",
    "    #if offsetPop > 0:   #... now include a splitPoly to nail the avg District Pop\n",
    "    #    isOver = True  #we slightly overshot.  ID the farthest-away tract for split-jettison\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], hdCPpop, neighborList)\n",
    "    #    HDvPop[t] = totPop - (1. - splitTractUse[t]) * tractPop[splitTractNo[t]]\n",
    "    #if offsetPop < 0:\n",
    "    #    isOver = False  #we have undershot.  Pick up the nearest contiguous tract that can be split to fill the gap\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], tractPop, neighborList)\n",
    "    #    HDtractList[t].append(splitTractNo[t])\n",
    "    #    HDvPop[t] = totPop + splitTractUse[t]*tractPop[splitTractNo[t]]       \n",
    "    #if abs(1. - HDvPop[t]/aDP) > 0.005 :  #something went wrong with pop assignation for this HD\n",
    "    #    print(\"WARNING! Total Home District pop was\",HDvPop[t],\"vs target\",aDP,\"for tract\",t)   ##### hdCP topology not yet known; skip partial\n",
    "        \n",
    "    HDPoly1[t] = dummyPoly  #tractGeom[t] #skip constructing the HD poly shape.  Do compute area of the Home District, including final partial\n",
    "    HDarea[t] = 0.\n",
    "    for tt in HDtractList[t]:\n",
    "        if tt == splitTractNo[t]:\n",
    "            tractUse[tt] += nDistricts * HDweight[t] * splitTractUse[t] \n",
    "            #HDarea[t]   += tractArea[tt] * splitTractUse[t]  #these are original (nonsquished) areas\n",
    "            \n",
    "        else:\n",
    "            tractUse[tt] += nDistricts * HDweight[t]\n",
    "            #HDarea[t]    += tractArea[tt]\n",
    "            #HDPoly1[t] = HDPoly1[t].union(tractGeom[tt])\n",
    "    HDPoly1[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t] )\n",
    "    #HDarea[t] = HDPoly1[t].area + splitTractUse[t] * tractArea[splitTractNo[t]]  \n",
    "    #if splitTractUse[t] > 0.5:\n",
    "    #    HDPoly1[t] = HDPoly1[t].union(tractGeom[splitTractNo[t]])\n",
    "                          \n",
    "    #ALL DONE ESTABLISHING THE FINAL HDTRACTLIST.  FINALIZE STATS\n",
    "totalTime = time.time() - codeStartTime\n",
    "print(r3(totalTime),\"seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\")\n",
    "n_bins=50\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"vtd avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()\n",
    "HDvPop = [np.sum([hdCPpop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.scatter([hdCPpop[t] for t in HDsToDraw],[HDvPop[t] for t in HDsToDraw] )\n",
    "print(\"here are your HD pops\")\n",
    "plt.axhline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "origHDHDtractList = [HDtractList[t].copy() for t in range(nHDs)] #save for posterity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "4c509805-0d01-46dd-9ed4-3c3833c6b0e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we will write the VRA-respecting polygon-based results to a file; uncomment last line to save to file\n"
     ]
    }
   ],
   "source": [
    "#last block of option 2 (i.e. generating polygonal HDs from scratch)\n",
    "DATE = \"06Jul\"\n",
    "print(\"Now we will write the VRA-respecting polygon-based results to a file; uncomment last line to save to file\")\n",
    "tractNo = [t for t in range(nHDs) ]\n",
    "HDangle0 = [HDangle[t][0] for t in range(nHDs) ]\n",
    "HDangle1 = [HDangle[t][1] for t in range(nHDs) ]\n",
    "HDangle2 = [HDangle[t][2] for t in range(nHDs) ]\n",
    "HDangle3 = [HDangle[t][3] for t in range(nHDs) ]\n",
    "HDradius0 = [HDradius[t][0] for t in range(nHDs)]\n",
    "HDradius1 = [HDradius[t][1] for t in range(nHDs)]\n",
    "HDradius2 = [HDradius[t][2] for t in range(nHDs)]\n",
    "HDradius3 = [HDradius[t][3] for t in range(nHDs)]\n",
    "hdCPx, hdCPy =   [hdCP[t].x for t in range(nHDs)], [hdCP[t].y for t in range(nHDs)]\n",
    "isVRAcore, isVRAenv = [0]*nHDs,[0]*nHDs\n",
    "polyHDtractList = [HDtractList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "for t in coreVTDs+envelopeVs:\n",
    "    HDtractList[t] = VRAvtdList[t].copy()\n",
    "    HDvPop[t] = np.sum([tractPop[v]  for v in HDtractList[t] ])\n",
    "    HDarea[t] = np.sum([tractArea[v] for v in HDtractList[t] ])\n",
    "    if t in coreVTDs:\n",
    "        isVRAcore[t] = 1\n",
    "    if t in envelopeVs:\n",
    "        isVRAenv[t]  = 1\n",
    "\n",
    "paramList = [\"STATE\",\"statePop\",\"nDistricts\",\"nHDs\",\"nWedges\",\"popn-toler\",\"levelL\", \"maxAngleRatio\",\n",
    "             \"maxAngle\",\"minAdjRatio\",\"maxUncap\", \"oppWt\", \"calc sec\",\"xScale\",\"outputs...\"]\n",
    "paramValues = [STATE,statePop, nDistricts, nHDs, nWedges, tolerPop, levelL, maxAngleRatio, maxAngle, minAdjRatio, maxUncap,\n",
    "               oppWt, totalTime, xScale, -777]\n",
    "for i in range(nHDs-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "HDdf = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"countyNo\":HDcountyNo,\n",
    "                    \"tractNo\":tractNo,\"centroid x\":hdCPx,\"centroid y\":hdCPy,\"tractPop\":hdCPpop,\n",
    "                    \"HDweight\":HDweight,\"HD-pop\":HDvPop,\"HDarea\":HDarea, \"countyNo\":countyNo,\n",
    "                    \"startAngle\":angle0,\"HDangle0\":HDangle0,\"HDangle1\":HDangle1,\"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\n",
    "                    \"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\"HDradius2\":HDradius2, \"HDradius3\":HDradius3,\"tractUse\":tractUse,\n",
    "                    \"splitTractNo\":splitTractNo,\"splitTractUse\":splitTractUse,\"HDtractList\":HDtractList,\n",
    "                    \"isVRAcore\":isVRAcore, \"isVRAenv\":isVRAenv}) \n",
    "\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Bnopatch\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeB\n",
    "outname = STATE+str(int(nHDs))+\"VRA_\"+str(int(nDistricts))+\"nW4_\"+DATE+\".csv\"  #solveWedgeC\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Buutpatch\"+str(int(nDistricts))+\"nW4.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "HDdf.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "cf747d9c-cf6d-420e-9c3c-6723619586ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "like nonVRA states, create HDunitLists based on each HD's tractList, with in-out for multiVTD units\n"
     ]
    }
   ],
   "source": [
    "#copy from vanilla HD for converting to unit lists, discontiguities, equalizing pop, equalizing use ...\n",
    "print(\"like nonVRA states, create HDunitLists based on each HD's tractList, with in-out for multiVTD units\")\n",
    "coldRestart = False\n",
    "if coldRestart:\n",
    "    infilename = input(\"enter the original HD polygon shape assignment csv, \"+ \n",
    "                       \"e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv\")\n",
    "    shapeDF = pd.read_csv(infilename)\n",
    "    HDvPop = shapeDF[\"HD-pop\"].to_list()\n",
    "    HDweight = shapeDF['HDweight'].to_list() #shapeDF['HDwt'].to_list() or #shapeDF['HDweight'].to_list()\n",
    "    HDarea = shapeDF['HDarea'].to_list()\n",
    "    #tractPop = shapeDF['tractPop'].to_list()   #we will use vtd-mapped pops instead\n",
    "    nHDs = len(shapeDF)\n",
    "    hdCPx = shapeDF['centroid x'].to_list()   #note: these may be translated from outcroppings into a convex representation of the map\n",
    "    hdCPy = shapeDF['centroid y'].to_list()\n",
    "    hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs) ]\n",
    "    HDtractListString = shapeDF[\"HDtractList\"]\n",
    "    HDtractList = [ast.literal_eval(HDtractListString[t]) for t in range(nHDs)]\n",
    "    isVRAcore = shapeDF['isVRAcore']\n",
    "    isVRAenv = shapeDF['isVRAenv']\n",
    "    HDpoly = [dummyPoly for t in range(nHDs)]\n",
    "    print(\"OK, I have read in the polygon-based results, ready to assign units\")\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001:\n",
    "        popHDlist.append(t)  #this now includes districts with VRA cores, as they may need triage\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2709311-793a-4804-baea-6f78817cfcc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"establishing which UNITS are in the core\")\n",
    "coreUnitPop, coreUs = 0., list()\n",
    "coreTractPoly = tractGeom[coreVTDs[0]]\n",
    "for v in coreVTDs[1:] :\n",
    "    coreTractPoly = coreTractPoly.union(tractGeom[v])\n",
    "for u in range(nUnits):\n",
    "    if coreTractPoly.contains(unitCP[u]):\n",
    "        coreUnitPop += unitPop[u]\n",
    "        coreUs.append(u)\n",
    "print(\"the final core unit pop is\",coreUnitPop,r5(coreUnitPop/aDP),\"of a district\")\n",
    "coreUset = set(coreUs)\n",
    "coreVset = set(coreVTDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "893b1d10-e125-4c97-b3b4-4dcaf7bd4dd8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vtd avg and sd usage are 1.00043 0.14174\n",
      "here are the tract uses\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops vs avg district pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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dd9e4jMPh0P3336+nnnpKhYWFmjdvngYOHKhu3brp8ssvt6ahQ4fK4/FoyZIl57inZ4dTSACApuXIHltux+Fw6J///Kfuu+8+9e3bV06nUzfeeKNmz559TutLTk7WvHnzNGDAAMXGxp7VMiNHjtQf//hHzZ49W2+//XaVAzM7nU4NHjxY8+bNU0pKyjm17Ww4zNkMH21D+fn5ioiIUF5ensLDwxu6OefPt5nSK9dKYzaefA5BLeoUlpSp09R3JUk7pycxGjUA2zpx4oT279+vdu3aKTg4+ORMnsTrN6r8//mvs/3+5hsKANA0eOJOhgnGQmoUCDAAgKbDE0egaCS4iBcAANgOR2BgcToc6npRhPUaAAB/RYCBJTjQpbfGXd3QzQAAoEacQgIANFqN9EZb26uL/xcCDACg0al4nH5h4Xm8ZRpnreL/5fRhD2qDU0iwFJWUK/G5jZKkdeOvVYjb1cAtAoBz43K55PF4rEEMQ0ND6310ZNTMGKPCwkJlZ2fL4/HI5Tr37xkCDCxGRodyi6zXAGBnMTExkuQzEjP8g8fjsf5/zhUBBgDQKDkcDrVu3VpRUVEqLS1t6ObgvwIDA3/UkZcKBBgAQKPmcrnq5AsT/oWLeAEAgO0QYAAAgO0QYAAAgO1wDQwsDjnUIaqZ9RoAAH9FgIElxO1S6vhrG7oZAADUiFNIAADAdggwAADAdggwsBSVlOsXz23UL57bqKKS8oZuDgAA1eIaGFiMjPZmF1ivAQDwVxyBAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtsNdSLA45NCFnhDrNQAA/ooAA0uI26UPH76+oZsBAECNOIUEAABshwADAABshwADy4nSct3y4ge65cUPdKKUoQQAAP6La2Bg8Rqjz/+TZ70GAMBfcQQGAADYDgEGAADYTq0DzKZNm3TzzTcrNjZWDodDq1at8ik3xmjq1Klq3bq1QkJClJiYqL179/rUycnJ0fDhwxUeHi6Px6Pk5GQVFBT41Pn88891zTXXKDg4WHFxcZo5c2bt9w4AADRKtQ4wx48fV7du3TRnzpwqy2fOnKlZs2Zp7ty5Sk9PV1hYmJKSknTixAmrzvDhw7Vjxw6lpqZq9erV2rRpk8aMGWOV5+fn64YbblCbNm2UkZGhZ555RtOmTdMrr7xyDrsIAAAam1pfxNu/f3/179+/yjJjjF544QVNnjxZgwYNkiQtXrxY0dHRWrVqlYYNG6Zdu3Zp7dq12rZtm3r16iVJmj17tgYMGKBnn31WsbGxWrJkiUpKSjR//ny53W517txZmZmZeu6553yCDgAAaJrq9BqY/fv3KysrS4mJida8iIgIxcfHKy0tTZKUlpYmj8djhRdJSkxMlNPpVHp6ulWnb9++crvdVp2kpCTt3r1bR48erXLbxcXFys/P95lQe5FhbkWGuWuuCABAA6rT26izsrIkSdHR0T7zo6OjrbKsrCxFRUX5NiIgQJGRkT512rVrV2kdFWXNmzevtO0ZM2bo0UcfrZsdaaJC3QH6ZMovGroZAADUqNHchTRp0iTl5eVZ08GDBxu6SQAAoJ7UaYCJiYmRJB0+fNhn/uHDh62ymJgYZWdn+5SXlZUpJyfHp05V6zh1G6cLCgpSeHi4zwQAABqnOg0w7dq1U0xMjNavX2/Ny8/PV3p6uhISEiRJCQkJys3NVUZGhlVnw4YN8nq9io+Pt+ps2rRJpaWlVp3U1FRdeumlVZ4+Qt04UVqu2/+Sptv/ksZQAgAAv1brAFNQUKDMzExlZmZKOnnhbmZmpg4cOCCHw6EHHnhAjz/+uN566y1t375dI0aMUGxsrG699VZJUseOHXXjjTdq9OjR2rp1qz788EONGzdOw4YNU2xsrCTp17/+tdxut5KTk7Vjxw4tX75cf/7znzV+/Pg623FU5jVG6ftzlL4/h6EEAAB+rdYX8X788cf6+c9/br2vCBUjR47UwoULNWHCBB0/flxjxoxRbm6urr76aq1du1bBwcHWMkuWLNG4cePUr18/OZ1ODRkyRLNmzbLKIyIi9N577yklJUU9e/ZUy5YtNXXqVG6hBgAAks4hwFx33XUyZ/jr3OFwaPr06Zo+fXq1dSIjI7V06dIzbqdr167avHlzbZsHAACagEZzFxIAAGg6CDAAAMB2CDAAAMB26vRJvLC/kEBXQzcBAIAaEWBgCXUHaNdjNzZ0MwAAqBGnkAAAgO0QYAAAgO0QYGA5UVquexZs1T0LtjKUAADAr3ENDCxeY/T+7u+t1wAA+CuOwAAAANshwAAAANshwAAAANshwAAAANshwAAAANshwAAAANvhNmpYQt0B+vqpgQ3dDAAAasQRGAAAYDsEGAAAYDsEGFhOlJbrt0sy9NslGQwlAADwawQYWLzGaM32LK3ZnsVQAgAAv0aAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtsNQArCEBLq0c3qS9RoAAH9FgIHF4XAo1M1HAgDg/ziFBAAAbIcAA0txWbl+//pn+v3rn6m4jKEEAAD+iwADS7nX6I1P/qM3PvmPyr0MJQAA8F8EGAAAYDsEGAAAYDsEGAAAYDvcM9uUHdnj+77U+7/XuYekqDbntz0AAJwlAkxTFNpCCgyVVo72nW+CJC04+fqVvtK4DyRP3HlvHgAANSHANEWeOCllq1T4g+/8Uq/08nf/fV10spwAAwDwQwSYpsoTVymchBijjMmdpawvFPK34gZqGAAANSPAwOJwONSiWZAU6pIcDd0aAACqx11IAADAdjgCA0txWbkeX71LOp6rySZAQQ3dIAAAqkGAgaXca/S3Ld9IkiYFuRq4NQAAVI9TSAAAwHYIMAAAwHYIMAAAwHYIMAAAwHbqPMCUl5drypQpateunUJCQnTJJZfosccekzHGqmOM0dSpU9W6dWuFhIQoMTFRe/fu9VlPTk6Ohg8frvDwcHk8HiUnJ6ugoKCumwsAAGyozgPM008/rZdfflkvvviidu3apaefflozZ87U7NmzrTozZ87UrFmzNHfuXKWnpyssLExJSUk6ceKEVWf48OHasWOHUlNTtXr1am3atEljxoyp6+YCAAAbqvPbqD/66CMNGjRIAwcOlCS1bdtWr732mrZu3Srp5NGXF154QZMnT9agQYMkSYsXL1Z0dLRWrVqlYcOGadeuXVq7dq22bdumXr16SZJmz56tAQMG6Nlnn1VsbGxdNxuSggNc2jzh51L2TgW/VtLQzQEAoFp1fgSmT58+Wr9+vfbs2SNJ+uyzz/TBBx+of//+kqT9+/crKytLiYmJ1jIRERGKj49XWlqaJCktLU0ej8cKL5KUmJgop9Op9PT0KrdbXFys/Px8nwm143Q6FBcZqrjwADkdpuYFAABoIHV+BObhhx9Wfn6+LrvsMrlcLpWXl+uJJ57Q8OHDJUlZWVmSpOjoaJ/loqOjrbKsrCxFRUX5NjQgQJGRkVad082YMUOPPvpoXe8OAADwQ3V+BOb111/XkiVLtHTpUn3yySdatGiRnn32WS1atKiuN+Vj0qRJysvLs6aDBw/W6/Yao5Iyr55cs0tPfpCnEsOTeAEA/qvOj8A89NBDevjhhzVs2DBJUpcuXfTNN99oxowZGjlypGJiYiRJhw8fVuvWra3lDh8+rO7du0uSYmJilJ2d7bPesrIy5eTkWMufLigoSEFBjN7zY5R5vXpl01eSpAeCAuRu4PYAAFCdOj8CU1hYKKfTd7Uul0ter1eS1K5dO8XExGj9+vVWeX5+vtLT05WQkCBJSkhIUG5urjIyMqw6GzZskNfrVXx8fF03GQAA2EydH4G5+eab9cQTT+jiiy9W586d9emnn+q5557TqFGjJEkOh0MPPPCAHn/8cXXo0EHt2rXTlClTFBsbq1tvvVWS1LFjR914440aPXq05s6dq9LSUo0bN07Dhg3jDiQAAFD3AWb27NmaMmWKfvvb3yo7O1uxsbEaO3aspk6datWZMGGCjh8/rjFjxig3N1dXX3211q5dq+DgYKvOkiVLNG7cOPXr109Op1NDhgzRrFmz6rq5AADAhhzm1EfkNiL5+fmKiIhQXl6ewsPDG7o558+3mdIr10pjNkqx3Wu1aGFJmTpNfVeStDPoHoWOfa/W6wAA4Mc42+9vxkICAAC2Q4ABAAC2U+fXwMC+ggNceu/BvlL2/yn4HwwlAADwXwQYWJxOh34afYFUHigxlAAAwI9xCgkAANgOR2BgKSnzas77+6Rj+UoxLp7ECwDwWwQYWMq8Xv15/V5J0liGEgAA+DFOIQEAANshwAAAANshwAAAANshwAAAANshwAAAANshwAAAANvhNmpYggJc+mfKz6QjexS0iqEEAAD+iwADi8vpULc4j+RyM5QAAMCvcQoJAADYDkdgYCkp82rBh/ul/GO6h6EEAAB+jAADS5nXqxnv/J8k6S6GEgAA+DFOIQEAANshwAAAANshwAAAANshwAAAANshwAAAANshwAAAANvhNmpYggJcem30VdIP+xT0NkMJAAD8FwEGFpfToYRLWkghBxlKAADg1ziFBAAAbIcjMLCUlnv12tYDUm6B7jAuBTZ0gwAAqAYBBpbScq+m/nOHJOmXQQEEGACA3+IUEgAAsB0CDAAAsB0CDAAAsB0CDAAAsB0CDAAAsB0CDAAAsB1uo4bF7XJq/t29pB/2y/1eaUM3BwCAahFgYAlwOXX9ZdHSt99JDm9DNwcAgGpxCgkAANgOR2BgKS33atWnh6Tc47qVoQQAAH6MAANLablXD/3jc0nSQIYSAAD4MU4hAQAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2yHAAAAA2+E2aljcLqfm/LqHdPRruTcwlAAAwH/VyxGYQ4cO6c4771SLFi0UEhKiLl266OOPP7bKjTGaOnWqWrdurZCQECUmJmrv3r0+68jJydHw4cMVHh4uj8ej5ORkFRQU1Edz8V8BLqcGdm2tgR1CFMBQAgAAP1bnAebo0aP62c9+psDAQL3zzjvauXOn/vSnP6l58+ZWnZkzZ2rWrFmaO3eu0tPTFRYWpqSkJJ04ccKqM3z4cO3YsUOpqalavXq1Nm3apDFjxtR1cwEAgA3V+Smkp59+WnFxcVqwYIE1r127dtZrY4xeeOEFTZ48WYMGDZIkLV68WNHR0Vq1apWGDRumXbt2ae3atdq2bZt69eolSZo9e7YGDBigZ599VrGxsXXdbEgqK/fq3R2HpaNFSjJOzi8CAPxWnR+Beeutt9SrVy/96le/UlRUlK644gq9+uqrVvn+/fuVlZWlxMREa15ERITi4+OVlpYmSUpLS5PH47HCiyQlJibK6XQqPT29yu0WFxcrPz/fZ0LtlJR7lbL0E6W8k6MSBhIAAPixOg8wX331lV5++WV16NBB7777ru69917df//9WrRokSQpKytLkhQdHe2zXHR0tFWWlZWlqKgon/KAgABFRkZadU43Y8YMRUREWFNcXFxd7xoAAPATdR5gvF6vevTooSeffFJXXHGFxowZo9GjR2vu3Ll1vSkfkyZNUl5enjUdPHiwXrcHAAAaTp0HmNatW6tTp04+8zp27KgDBw5IkmJiYiRJhw8f9qlz+PBhqywmJkbZ2dk+5WVlZcrJybHqnC4oKEjh4eE+EwAAaJzqPMD87Gc/0+7du33m7dmzR23atJF08oLemJgYrV+/3irPz89Xenq6EhISJEkJCQnKzc1VRkaGVWfDhg3yer2Kj4+v6yYDAACbqfMbTR588EH16dNHTz75pIYOHaqtW7fqlVde0SuvvCJJcjgceuCBB/T444+rQ4cOateunaZMmaLY2Fjdeuutkk4esbnxxhutU0+lpaUaN26chg0bxh1IAACg7gPMlVdeqTfffFOTJk3S9OnT1a5dO73wwgsaPny4VWfChAk6fvy4xowZo9zcXF199dVau3atgoODrTpLlizRuHHj1K9fPzmdTg0ZMkSzZs2q6+YCAAAbchhjTEM3oj7k5+crIiJCeXl5Tet6mG8zpVeulcZslGK712rR0nKvVn16SMo9oFs336zAsRtqvQ4AAH6Ms/3+5lllsAS6nPpVrzjp2x+kD8obujkAAFSL0agBAIDtcAQGlrJyrzbt/V764YT6MpQAAMCP8R0FS0m5V6MWnhw1fGdQIB8OAIDf4hQSAACwHQIMAACwHQIMAACwHQIMAACwHQIMAACwHQIMAACwHe6UhSXQ5dT0QZ2l3P8ocEtZQzcHAIBqEWBgCXQ5NSKhrfRtrpTOUAIAAP9FgEH1juypviy0heSJO39tAQDgFAQYWMq9Rlv350gFQeodECbXytHVVw4MlVK2EmIAAA2CAANLcVm57nh1iyRp5/g0hZYdrbrikT3SytFS4Q8EGABAgyDAoGqeCyV3m4ZuBQAAVeI2agAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDvchQRLgNOpSf0vs14DAOCvCDCwuAOcGnvtJQ3dDAAAasSf2QAAwHY4AgNLudfoi0N5kqTLL4yQy+lo4BYBAFA1jsDAUlxWrkFzPtSgOR+quIzRqAEA/osAAwAAbIcAAwAAbIcAAwAAbIcAAwAAbIcAAwAAbIcAAwAAbIfnwMAS4HTqd/06WK8BAPBXBBhY3AFOPfiLnzZ0MwAAqBF/ZgMAANvhCAwsXq/Rvu8LJEntWzWTk6EEAAB+igADy4myct3w/CZJ0s7pSQp18/EAAPgnTiEBAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADb4T5ZWAKcTo3p+xPrNQAA/ooAA4s7wKk/DOjY0M0AAKBG/JkNAABsp94DzFNPPSWHw6EHHnjAmnfixAmlpKSoRYsWatasmYYMGaLDhw/7LHfgwAENHDhQoaGhioqK0kMPPaSysrL6bm6T5vUaHcwp1MGcQnm9pqGbAwBAteo1wGzbtk1/+ctf1LVrV5/5Dz74oP71r39pxYoV2rhxo7799lvddtttVnl5ebkGDhyokpISffTRR1q0aJEWLlyoqVOn1mdzm7wTZeW6Zub7umbm+zpRVt7QzQEAoFr1FmAKCgo0fPhwvfrqq2revLk1Py8vT/PmzdNzzz2n66+/Xj179tSCBQv00UcfacuWLZKk9957Tzt37tTf//53de/eXf3799djjz2mOXPmqKSkpL6aDAAAbKLeAkxKSooGDhyoxMREn/kZGRkqLS31mX/ZZZfp4osvVlpamiQpLS1NXbp0UXR0tFUnKSlJ+fn52rFjR5XbKy4uVn5+vs8EAAAap3q5C2nZsmX65JNPtG3btkplWVlZcrvd8ng8PvOjo6OVlZVl1Tk1vFSUV5RVZcaMGXr00UfroPUAAMDf1fkRmIMHD+p3v/udlixZouDg4LpefbUmTZqkvLw8azp48OB52zYAADi/6jzAZGRkKDs7Wz169FBAQIACAgK0ceNGzZo1SwEBAYqOjlZJSYlyc3N9ljt8+LBiYmIkSTExMZXuSqp4X1HndEFBQQoPD/eZAABA41TnAaZfv37avn27MjMzralXr14aPny49TowMFDr16+3ltm9e7cOHDighIQESVJCQoK2b9+u7Oxsq05qaqrCw8PVqVOnum4yAACwmTq/BuaCCy7Q5Zdf7jMvLCxMLVq0sOYnJydr/PjxioyMVHh4uO677z4lJCToqquukiTdcMMN6tSpk+666y7NnDlTWVlZmjx5slJSUhQUFFTXTcZ/uZwO3XVVG+s1AAD+qkGGEnj++efldDo1ZMgQFRcXKykpSS+99JJV7nK5tHr1at17771KSEhQWFiYRo4cqenTpzdEc5uMoACXHrv18porAgDQwM5LgPn3v//t8z44OFhz5szRnDlzql2mTZs2WrNmTT23DAAA2BGDOcJijFHO8ZMPCowMc8vh4DQSAMA/EWBgKSotV8/H10mSdk5PUqibjwcAwD/xDYVzd2RP9WWhLSRP3PlrCwCgSSHAoPZCW0iBodLK0dXXCQyVUrYSYgAA9YIAg9rzxJ0MJ4U/VF1+ZM/JcFP4AwEGAFAvCDA4N544wgkAoMHU22jUAAAA9YUAAwAAbIdTSLC4nA4N6XGR9RoAAH9FgIElKMClPw3t1tDNAACgRpxCAgAAtsMRGFiMMSoqLZckhQS6GEoAAOC3OAIDS1FpuTpNfVedpr5rBRkAAPwRAQYAANgOAQYAANgOAQYAANgOAQYAANgOAQYAANgOAQYAANgOz4GBxelwaECXGOs1AAD+igADS3CgSy8N79nQzQAAoEacQgIAALZDgAEAALZDgIGlsKRMbR9+W20ffluFJWUN3RwAAKpFgAEAALZDgAEAALZDgAEAALZDgAEAALZDgAEAALZDgAEAALbDk3hhcToc+vmlrazXAAD4KwIMLMGBLi24p3dDNwMAgBpxCgkAANgOAQYAANgOAQaWwpIydZyyVh2nrGUoAQCAX+MaGPgoKi1v6CYAAFAjjsAAAADbIcAAAADb4RQS6s+RPdWXhbaQPHHnry0AgEaFAIO6F9pCCgyVVo6uvk5gqJSylRADADgnBBjUPU/cyXBS+EPV5Uf2nAw3hT8QYAAA54QAA4vT4VB8u0jr9Y/iiSOcAADqDQEGluBAl5aPTWjoZgAAUCPuQgIAALZDgAEAALZDgIGlsKRMPR5LVY/HUhlKAADg17gGBj5yjpc0dBMAAKhRnR+BmTFjhq688kpdcMEFioqK0q233qrdu3f71Dlx4oRSUlLUokULNWvWTEOGDNHhw4d96hw4cEADBw5UaGiooqKi9NBDD6msjKMCAACgHgLMxo0blZKSoi1btig1NVWlpaW64YYbdPz4cavOgw8+qH/9619asWKFNm7cqG+//Va33XabVV5eXq6BAweqpKREH330kRYtWqSFCxdq6tSpdd1cAABgQ3V+Cmnt2rU+7xcuXKioqChlZGSob9++ysvL07x587R06VJdf/31kqQFCxaoY8eO2rJli6666iq999572rlzp9atW6fo6Gh1795djz32mCZOnKhp06bJ7XbXdbMBAICN1PtFvHl5eZKkyMiTD0jLyMhQaWmpEhMTrTqXXXaZLr74YqWlpUmS0tLS1KVLF0VHR1t1kpKSlJ+frx07dlS5neLiYuXn5/tMAACgcarXAOP1evXAAw/oZz/7mS6//HJJUlZWltxutzwej0/d6OhoZWVlWXVODS8V5RVlVZkxY4YiIiKsKS6Op8ACANBY1WuASUlJ0RdffKFly5bV52YkSZMmTVJeXp41HTx4sN632dg4HQ51vShCXS+K+PFDCQAAUI/q7TbqcePGafXq1dq0aZMuuugia35MTIxKSkqUm5vrcxTm8OHDiomJseps3brVZ30VdylV1DldUFCQgoKC6ngvmpbgQJfeGnd1QzcDAIAa1fkRGGOMxo0bpzfffFMbNmxQu3btfMp79uypwMBArV+/3pq3e/duHThwQAkJJ8fhSUhI0Pbt25WdnW3VSU1NVXh4uDp16lTXTQYAADZT50dgUlJStHTpUv3zn//UBRdcYF2zEhERoZCQEEVERCg5OVnjx49XZGSkwsPDdd999ykhIUFXXXWVJOmGG25Qp06ddNddd2nmzJnKysrS5MmTlZKSwlEWAABQ9wHm5ZdfliRdd911PvMXLFigu+++W5L0/PPPy+l0asiQISouLlZSUpJeeuklq67L5dLq1at17733KiEhQWFhYRo5cqSmT59e183FKYpKypX43EZJ0rrx1yrE7WrgFgEAULU6DzDGmBrrBAcHa86cOZozZ061ddq0aaM1a9bUZdNQAyOjQ7lF1msAAPwVgzkCAADbIcAAAADbIcAAAADbIcAAAADbIcAAAADbqbcn8cJ+HHKoQ1Qz6zUAAP6KAANLiNul1PHXNnQzAACoEaeQAACA7RBgAACA7RBgYCkqKdcvntuoXzy3UUUl5Q3dHAAAqsU1MLAYGe3NLrBe17sje85cHtpC8sTVfzsAALZDgMH5F9pCCgyVVo4+c73AUCllKyEGAFAJAQbnnyfuZDAp/KH6Okf2nAw4hT8QYAAAlRBg0DA8cQQTAMA54yJeAABgOxyBgX8704W+XOQLAE0WAQYWhxy60BNivW5QZ3OhLxf5AkCTRYCBJcTt0ocPX9/QzTippgt9ucgXAJo0Agz8Fxf6AgCqwUW8AADAdggwsJwoLdctL36gW178QCdKGUoAAOC/OIUEi9cYff6fPOs1AAD+iiMwAADAdggwAADAdggwAADAdggwAADAdggwAADAdrgLCT4iw9wN3QQAAGpEgIEl1B2gT6b8oqGbAQBAjQgwsDdGqwaAJokAA3titGoAaNIIMLCcKC3XyPlbJUmLRvVWcKCrgVt0BoxWDQBNGgEGFq8xSt+fY732e4xWDQBNFrdRAwAA2yHAAAAA2+EUEho37lICgEaJAIPGibuUAKBRI8CgceIuJQBo1Agw8BHiz7dO1xZ3KQFAo0WAgSXUHaBdj93Y0M04v7hGBgBsiQDTiBzKLVLR9wVq39ANsQOukQEAWyPANBKHcouU+KeN+knZPr0dJGUXFCvqtPKjx0skSc3D3LrQE9IwDT2Dijaebft+1D5xjQwA2BoBxs+c+qVcoaov59O/7I8eL1FRabmG9Y6TPpfyi0qtAFMRbopKyyWdvM5l3e+vrbTOE6XluvfvGZKkl+/sqR+Ol9QqUJzLflas+9Q2Vte+05c/m306I66RAQDbIsDUkbo4wnH6l3KFkECX5t7VUy3C3JKkH46X6Dd/y7C+7Ofe1dPadtQFQZXWWxFuXri9uyTpgeWZVv1Tw9KJ0nK9v/t7SdKmPd/rd8syfbZRsf3a7uPZhJWKNt53fXvN3rBPR4+XVLv+Q7lF2rY/p8p98scjSwCAukeA+ZEO5RZpX3aBFSik/wWO9lHNrC/Uszk9cmrQaB/VTNL/wkrFIIsVQgJdeuH27pq0crtVFhLo0gUhgVW2T5K1zor5v5qbViksVRjzt4wqt3Hq9iuOeFS1bxXzqgtbp4aVbf8df0mStXxFm08NPVWt78p2kVYIq1imQp0cOTrTRb4SF/oCQAMhwJyD6r5MF43qLUlW4Kj4wq6YV93RjAqnBo3LL4yw5lccoThVxZfzqV/gzcPcKvrm5CmggzlFOrTne5/tNg9zW3W/OJRXKSydKC3XL+emSZL+8ZsEtfaEVNpGRTsfWJ6pbftztC/MXWnfTt1fqfqw1fenrfTXzfv1wPJMa94lUc0UEujymTfjti6atHK7z/oWjertExBPXaZCVUHyrJ3NRb5SzRf65h6s/jqbiu0QgACg1hzG+O+ww3PmzNEzzzyjrKwsdevWTbNnz1bv3r3Patn8/HxFREQoLy9P4eHhddamqq69qOpoS1VHZU7/Iq7KOV3LcYrsPemKWnqDBhY/oR2mXaX2nelak8KSMnWa+q4kaef0JIW6q863VfVBVSGjIqidfhRFqnxkpap5VR29OXV9p7fp1JB1+rLn1Kc1hY+KC31ve1Vq+dPK5YVHpOV3SaWF1a+DO50AwMfZfn/7bYBZvny5RowYoblz5yo+Pl4vvPCCVqxYod27dysqKqrG5esrwHxxKE83zf7AOnJxptMUNX1hV+VHn/b4NlN65VrtG/y2TrTsclYXAFc42wBzNvtWVxf+1vbOpNOX3bY/Rw8szzyr/69ayz0ozeldc0C5/W9SaMvKZTUFIIkjNACanLP9/vbbU0jPPfecRo8erXvuuUeSNHfuXL399tuaP3++Hn744QZuXeXTPFW58L+nYGqaVx/at2omxVbdvrpow/natx+zzgs9IVK7yEqnpM75tNLparoVWzpzADnbZ9FUF4DOZhuSPU5j2aGN/oB+wvnk5583vwwwJSUlysjI0KRJk6x5TqdTiYmJSktLq3KZ4uJiFRcXW+/z8vIknUxydangWL68xYUqOJav/HxHna67ThwrkIrNyX9rue+FJWXyFp88mpCfn6+yMxyBsYsLnNKbo69QbmGJcgpL9cCyT3XXy/9WcKBTLwy7QpGhgTWv5L9aNQtSq/Bg35nOCKnZmYNstf8PzgjprvVSUU7V5YU/SCvHSPNuO/P6A0Kk2145+cukunWUFZ3b8ueDHdroD+gnnE9n+3kb/b7kuahON13xvV3jCSLjhw4dOmQkmY8++shn/kMPPWR69+5d5TKPPPKIkcTExMTExMTUCKaDBw+eMSvY/0/s/5o0aZLGjx9vvfd6vcrJyVGLFi3kcNTuSEl+fr7i4uJ08ODBOr1+prGgf86M/jkz+qd69M2Z0T9n1lj6xxijY8eOKTY29oz1/DLAtGzZUi6XS4cPH/aZf/jwYcXExFS5TFBQkIKCfB/i5vF4flQ7wsPDbf0hqG/0z5nRP2dG/1SPvjkz+ufMGkP/RERE1FjHeR7aUWtut1s9e/bU+vXrrXler1fr169XQkJCA7YMAAD4A788AiNJ48eP18iRI9WrVy/17t1bL7zwgo4fP27dlQQAAJouvw0wt99+u77//ntNnTpVWVlZ6t69u9auXavo6Oh633ZQUJAeeeSRSqekcBL9c2b0z5nRP9Wjb86M/jmzptY/fvsgOwAAgOr45TUwAAAAZ0KAAQAAtkOAAQAAtkOAAQAAtmPLANO2bVs5HI5KU0pKilUnLS1N119/vcLCwhQeHq6+ffuqqKjojOt46qmnfLbz+eef65prrlFwcLDi4uI0c+bMSm1ZsWKFLrvsMgUHB6tLly5as2aNT7kxRlOnTlXr1q0VEhKixMRE7d27t457xNeZ+ufrr7+usszhcGjFihXWOg4cOKCBAwcqNDRUUVFReuihh1RWVuaznX//+9/q0aOHgoKC1L59ey1cuLBSW+bMmaO2bdsqODhY8fHx2rp1q0/5iRMnlJKSohYtWqhZs2YaMmRIpQcY1rW66J+qypctW+azHTv2T00/W1lZWbrrrrsUExOjsLAw9ejRQ2+88YbPOnJycjR8+HCFh4fL4/EoOTlZBQUFPnUa48+WdHb901R/90jSl19+qcGDB6tVq1YKDw/X0KFDK32em/Ln52z6pzF/fmrtRw9c1ACys7PNd999Z02pqalGknn//feNMcZ89NFHJjw83MyYMcN88cUX5v/+7//M8uXLzYkTJ6x1tGnTxkyfPt1nPQUFBVZ5Xl6eiY6ONsOHDzdffPGFee2110xISIj5y1/+YtX58MMPjcvlMjNnzjQ7d+40kydPNoGBgWb79u1WnaeeespERESYVatWmc8++8zccsstpl27dqaoqKhB+qesrMyn7LvvvjOPPvqoadasmTl27JgxxpiysjJz+eWXm8TERPPpp5+aNWvWmJYtW5pJkyZZ2/jqq69MaGioGT9+vNm5c6eZPXu2cblcZu3atVadZcuWGbfbbebPn2927NhhRo8ebTwejzl8+LBV5ze/+Y2Ji4sz69evNx9//LG56qqrTJ8+feqtb+qif4wxRpJZsGCBT71T/0/t2j81/Wz94he/MFdeeaVJT083X375pXnssceM0+k0n3zyibWOG2+80XTr1s1s2bLFbN682bRv397ccccdVnlj/dk62/5pqr97CgoKzE9+8hMzePBg8/nnn5vPP//cDBo0yFx55ZWmvLzcWkdT/fycbf805s9PbdkywJzud7/7nbnkkkuM1+s1xhgTHx9vJk+efMZl2rRpY55//vlqy1966SXTvHlzU1xcbM2bOHGiufTSS633Q4cONQMHDvRZLj4+3owdO9YYY4zX6zUxMTHmmWeescpzc3NNUFCQee211856/36s0/vndN27dzejRo2y3q9Zs8Y4nU6TlZVlzXv55ZdNeHi41R8TJkwwnTt39lnP7bffbpKSkqz3vXv3NikpKdb78vJyExsba2bMmGGMOdkXgYGBZsWKFVadXbt2GUkmLS3tR+xx7dS2f4w5GWDefPPNatfZWPrn9L4JCwszixcv9qkTGRlpXn31VWOMMTt37jSSzLZt26zyd955xzgcDnPo0CFjTOP+2aqpf4xpur973n33XeN0Ok1eXp5PmxwOh0lNTTXGNO3Pz9n0jzFN6/NTE1ueQjpVSUmJ/v73v2vUqFFyOBzKzs5Wenq6oqKi1KdPH0VHR+vaa6/VBx98UGnZp556Si1atNAVV1yhZ555xucUSVpamvr27Su3223NS0pK0u7du3X06FGrTmJios86k5KSlJaWJknav3+/srKyfOpEREQoPj7eqlPfTu+f02VkZCgzM1PJycnWvLS0NHXp0sXnoYFJSUnKz8/Xjh07rDpn2veSkhJlZGT41HE6nUpMTLTqZGRkqLS01KfOZZddposvvtiv+6dCSkqKWrZsqd69e2v+/Pk+Q783hv6pqm/69Omj5cuXKycnR16vV8uWLdOJEyd03XXXSTq53x6PR7169bLWk5iYKKfTqfT0dKtOY/3Zqql/KjTF3z3FxcVyOBw+D1kLDg6W0+m0fj835c/P2fRPhabw+Tkbtg8wq1atUm5uru6++25J0ldffSVJmjZtmkaPHq21a9eqR48e6tevn8/5u/vvv1/Lli3T+++/r7Fjx+rJJ5/UhAkTrPKsrKxKT/2teJ+VlXXGOqeWn7pcVXXq2+n9c7p58+apY8eO6tOnjzXvx+x7fn6+ioqKdOTIEZWXl9fYP263u9Kgm/7eP5I0ffp0vf7660pNTdWQIUP029/+VrNnz7bKG0P/VNU3r7/+ukpLS9WiRQsFBQVp7NixevPNN9W+fXurzVFRUT7rCQgIUGRkZI2fnYqyM9Xx95+tmvpHarq/e6666iqFhYVp4sSJKiws1PHjx/X//t//U3l5ub777jur3U3183M2/SM1nc/P2fDboQTO1rx589S/f39r2G2v1ytJGjt2rDVu0hVXXKH169dr/vz5mjFjhqSTYy1V6Nq1q9xut8aOHasZM2Y0qscwn94/pyoqKtLSpUs1ZcqUBmiZfzjX/jl13hVXXKHjx4/rmWee0f3331+v7T2fquqbKVOmKDc3V+vWrVPLli21atUqDR06VJs3b1aXLl0asLXn37n2T1P93dOqVSutWLFC9957r2bNmiWn06k77rhDPXr0kNNp+7+la+1c+6epfH7Ohq0DzDfffKN169Zp5cqV1rzWrVtLkjp16uRTt2PHjjpw4EC164qPj1dZWZm+/vprXXrppYqJial09XfF+5iYGOvfquqcWl4xr6JdFe+7d+9em109J1X1z6n+8Y9/qLCwUCNGjPCZHxMTU+lumLPd9/DwcIWEhMjlcsnlctXYPyUlJcrNzfU5ynBqnfp0rv1Tlfj4eD322GMqLi5WUFCQ7funqr758ssv9eKLL+qLL75Q586dJUndunXT5s2bNWfOHM2dO1cxMTHKzs72WVdZWZlycnJq/OxUlJ2pjj//bJ1N/1SlKf3uueGGG/Tll1/qyJEjCggIkMfjUUxMjH7yk59Y7W6qnx+p5v6pSmP8/JwtW8feBQsWKCoqSgMHDrTmtW3bVrGxsdq9e7dP3T179qhNmzbVriszM1NOp9M6fJmQkKBNmzaptLTUqpOamqpLL71UzZs3t+qsX7/eZz2pqalKSEiQJLVr104xMTE+dfLz85Wenm7VqU9V9c+p5s2bp1tuuUWtWrXymZ+QkKDt27f7/CJJTU1VeHi4FQxr2ne3262ePXv61PF6vVq/fr1Vp2fPngoMDPSps3v3bh04cMCv+6cqmZmZat68ufUXkN37p6q+KSwslKRKfy27XC7ryGdCQoJyc3OVkZFhlW/YsEFer1fx8fFWncb4s3U2/VOVpvi7p2XLlvJ4PNqwYYOys7N1yy23SGran59TVdc/VWmMn5+z1tBXEZ+r8vJyc/HFF5uJEydWKnv++edNeHi4WbFihdm7d6+ZPHmyCQ4ONvv27TPGnLzN+vnnnzeZmZnmyy+/NH//+99Nq1atzIgRI6x15ObmmujoaHPXXXeZL774wixbtsyEhoZWuhUtICDAPPvss2bXrl3mkUceqfJWNI/HY/75z39at8Wdj1vRztQ/xhizd+9e43A4zDvvvFOprOI26htuuMFkZmaatWvXmlatWlV5G/VDDz1kdu3aZebMmVPlbcJBQUFm4cKFZufOnWbMmDHG4/H43N30m9/8xlx88cVmw4YN5uOPPzYJCQkmISGhDnuiaj+mf9566y3z6quvmu3bt5u9e/eal156yYSGhpqpU6dadezcP9X1TUlJiWnfvr255pprTHp6utm3b5959tlnjcPhMG+//bZV78YbbzRXXHGFSU9PNx988IHp0KGDz22wjfVn62z6p6n/7pk/f75JS0sz+/btM3/7299MZGSkGT9+vE+dpvr5Mabm/mkKn5/asG2Aeffdd40ks3v37irLZ8yYYS666CITGhpqEhISzObNm62yjIwMEx8fbyIiIkxwcLDp2LGjefLJJ32eE2OMMZ999pm5+uqrTVBQkLnwwgvNU089VWk7r7/+uvnpT39q3G636dy5s88vcmNO3o42ZcoUEx0dbYKCgky/fv2qbXNdqql/Jk2aZOLi4nyeL3Cqr7/+2vTv39+EhISYli1bmt///vemtLTUp877779vunfvbtxut/nJT35iFixYUGk9s2fPNhdffLFxu92md+/eZsuWLT7lRUVF5re//a1p3ry5CQ0NNYMHDzbffffdue10LfyY/nnnnXdM9+7dTbNmzUxYWJjp1q2bmTt3bqW6du2fM/XNnj17zG233WaioqJMaGio6dq1a6Xbhn/44Qdzxx13mGbNmpnw8HBzzz33+DxDx5jG+7NVU/809d89EydONNHR0SYwMNB06NDB/OlPf6r0+IKm/PmpqX+awuenNhzGnHLvJwAAgA3Y+hoYAADQNBFgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7RBgAACA7fx/bt0STgsxXJ4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#this block added on rerun\n",
    "#HDweight = [tractPop[t]/statePop for t in range(nHDs)]\n",
    "#polyHDtractList = [HDtractList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "#for t in coreVTDs+envelopeVs:\n",
    "#    HDtractList[t] = VRAvtdList[t].copy()  #overwrite\n",
    "\n",
    "tractUse = [0.]*nHDs\n",
    "for t in range(nHDs):\n",
    "    for tt in HDtractList[t]:\n",
    "        tractUse[tt] += HDweight[t]*nDistricts\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"vtd avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "\n",
    "plt.hist([tractUse[t] for t in coreVTDs],weights=[HDweight[t] for t in coreVTDs],label=\"VRA\",histtype=\"step\")\n",
    "plt.hist([tractUse[t] for t in envelopeVs],weights=[HDweight[t] for t in envelopeVs],label=\"envel\",histtype=\"step\")\n",
    "plt.hist([tractUse[t] for t in HDsToDraw],weights=[HDweight[t] for t in HDsToDraw],label=\"other\",histtype=\"step\")\n",
    "plt.legend()\n",
    "print(\"here are the tract uses\")\n",
    "plt.show()\n",
    "\n",
    "HDvPop = [np.sum([tractPop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in coreVTDs+envelopeVs],label=\"VRA\",bins=50 ,histtype=\"step\")\n",
    "plt.hist([HDvPop[t] for t in HDsToDraw],label=\"nonVRA\",bins=50,histtype=\"step\" )\n",
    "plt.legend()\n",
    "print(\"here are your HD pops vs avg district pop\")\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "03188569-f9dc-41c7-9fa1-ac7466e59e1b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and now the tract uses\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"and now the tract uses\")\n",
    "plt.hist([tractUse[t] for t in coreVTDs], label=\"core\",histtype=\"step\")\n",
    "plt.hist([tractUse[t] for t in envelopeVs], label=\"env\",histtype=\"step\")\n",
    "plt.hist([tractUse[t] for t in HDsToDraw], label=\"other\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "7dc442f0-67ec-48ef-8269-47f45c22c5f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight))  \n",
    "#sumWt = np.sum(HDweight)  #uncomment to renormalize\n",
    "#HDweight = [HDweight[t]/sumWt for t in range(nHDs) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "8c6c4a61-658d-4379-a367-0c1b613a284d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "readying for vtd --> unit conversion of HDtractLists ...\n"
     ]
    }
   ],
   "source": [
    "nCCBs = len(CCBlist)\n",
    "CCBpopFrac = [[0. for j in range(nCCBs) ]  for t in range(nHDs)]\n",
    "\n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "CCBpopFrac = [[0. for j in range(nCCBs) ]  for t in range(nHDs)]\n",
    "print(\"readying for vtd --> unit conversion of HDtractLists ...\")\n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "26102ca2-79c1-48db-b873-7fa3a1553911",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\n",
      "working on vtd --> unit conversion for HD 1 last HD had pop 600765.855\n",
      "working on vtd --> unit conversion for HD 1001 last HD had pop 657480.0\n",
      "working on vtd --> unit conversion for HD 2001 last HD had pop 602675.0\n",
      "working on vtd --> unit conversion for HD 3001 last HD had pop 770101.0\n",
      "working on vtd --> unit conversion for HD 4001 last HD had pop 773237.003\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\" )\n",
    "HDunitList = [ list() for t in range(nHDs) ]\n",
    "for t in range(nHDs):\n",
    "    if t %1000 == 1:\n",
    "        print(\"working on vtd --> unit conversion for HD\",t,\"last HD had pop\",r3( np.sum([unitPop[u] for u in HDunitList[t-1]]) ) )\n",
    "    capturedCountyPop = [0. for c in range(nCounties)]\n",
    "    capturedCCBpop = [0. for i in range(nCCBs)]\n",
    "    for v in HDtractList[t]:\n",
    "        c = HDcountyNo[v]\n",
    "        if c in range(nCounties):  #we assigned countyno = -999 to unpopulated tracts\n",
    "            if c in unitCounties:\n",
    "                capturedCountyPop[c] += tractPop[v]\n",
    "            elif c in allFusedCounties:\n",
    "                for i, L in enumerate(CCBlist):\n",
    "                    if c in L:\n",
    "                        capturedCCBpop[i] += tractPop[v]\n",
    "            else:  #this vtd not part of a unit or fused county.  Could be split into fragments\n",
    "                for u in countyUnitList[c]:\n",
    "                    if unitParentVTDno[u] == v :  #we assign all units = vtd fragments from this HDTL-captured vtd\n",
    "                        HDunitList[t].append(u)\n",
    "    for c in unitCounties:\n",
    "        if capturedCountyPop[c] > 0.5 * countyPop[c]:\n",
    "            HDunitList[t].append(allUnits.index(c+0.5))\n",
    "    for i in range(nCCBs):  #don't yet assign in/out CCBs.  We'll do so in below block.  Just update max possible use for each CCB\n",
    "        CCBpopFrac[t][i] = capturedCCBpop[i] / CCBpop[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "a0979005-e316-43fa-9009-3340307c0e35",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing conversion to units.  Determine each CCB's use if we add it to all adjoining HDs\n",
      "CCBno 0 with pop 161018.0 would be used 1.764 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 1 with pop 185562.0 would be used 2.015 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 2 with pop 139686.0 would be used 1.384 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 3 with pop 25126.0 would be used 1.311 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if we are not allowed to use multiple CCB's in a single HD 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCBno 0 with pop 161018.0 would be used 1.7635316697409056 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 1 with pop 185562.0 would be used 2.01493928508819 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 2 with pop 139686.0 would be used 1.3844757838169277 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 3 with pop 25126.0 would be used 1.3114349463591106 if we added it to all adjoining districts with no 2-CCB districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing conversion to units.  Determine each CCB's use if we add it to all adjoining HDs\")\n",
    "CCBwouldUse = [0. for i in range(nCCBs)]\n",
    "CCBaddCandidates = [list() for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    jNo = allUnits.index(j+0.25)\n",
    "    ccbNbrSet = set(unitNbrs[jNo])\n",
    "    withCCBpopRat = list()\n",
    "    for t in range(nHDs):\n",
    "        if len(ccbNbrSet.intersection(set(HDunitList[t]))) > 0:\n",
    "            CCBwouldUse[j] += HDweight[t] * nDistricts\n",
    "            CCBaddCandidates[j].append(t)\n",
    "            withCCBpopRat.append((np.sum([unitPop[u] for u in HDunitList[t]]) + CCBpop[j]) / aDP )\n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",r3(CCBwouldUse[j]),\"if we added it to all adjoining districts\")\n",
    "    print(\"Here is the histogram of relative district pop with these added\")\n",
    "    plt.hist(withCCBpopRat,histtype=\"step\",label=\"CCB \"+str(j))\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "avoidMultiCCBuse = int(input(\"enter 1 if we are not allowed to use multiple CCB's in a single HD\"))  #option by state\n",
    "if avoidMultiCCBuse == 1:\n",
    "    for j in range(nCCBs):  #this block -- preventing HDs from picking up multiple CCB's; instead, pick up the closest one  \n",
    "        jNo = allUnits.index(j+0.25)\n",
    "        for jj in range(j+1, nCCBs):\n",
    "            jjNo = allUnits.index(j+0.25)\n",
    "            for t in CCBaddCandidates[j].copy():\n",
    "                if t in CCBaddCandidates[j]:\n",
    "                    if t in CCBaddCandidates[jj].copy():\n",
    "                        dist_j, dist_jj = hdCP[t].distance(unitCP[jNo]), hdCP[t].distance(unitCP[jjNo])\n",
    "                        if dist_j > dist_jj:\n",
    "                            CCBaddCandidates[j].remove(t)  #for MN, don't allow any districts with two CCB's\n",
    "                            CCBwouldUse[j] -= HDweight[t] * nDistricts\n",
    "                        else:\n",
    "                            CCBaddCandidates[jj].remove(t)\n",
    "                            CCBwouldUse[jj] -= HDweight[t] * nDistricts\n",
    "for j in range(nCCBs):    \n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",CCBwouldUse[j],\n",
    "          \"if we added it to all adjoining districts with no 2-CCB districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "a03c4b9d-69f7-4d3b-9c18-87c9680fc3b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 0 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 0 is 1.02193 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 1 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 1 is 1.02364 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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smF544QX96Ec/0k9/+lM98sgjkqRAICBJ8vl8Yffz+XzOvk9qbW1VKBQKuwEAgLNXxP/E09HRoXHjxunOO++UJI0ZM0a7du3SqlWrVFpaelrHrKys1G233RbJaQIAAItF/ApKRkaGRo4cGbZtxIgR2r9/vyTJ7/dLkpqamsLGNDU1Ofs+qaKiQsFg0Lk1NjZGetoAAMAiEQ+USy+9VPX19WHb3nrrLQ0ePFjSf58w6/f7VV1d7ewPhUKqra1Vfn5+p8d0u93yeDxhNwAAcPaK+J94br75Zl1yySW68847dc0112jr1q164IEH9MADD0iSXC6XZs+erTvuuEPDhg1TTk6OFixYoMzMTE2dOjXS0wEAADEo4oHypS99SU899ZQqKip0++23KycnR0uXLlVJSYkzZu7cuTpy5IhmzpyplpYWTZgwQVVVVUpKSor0dAAAQAxyGWNMtCfRU6FQSF6vV8FgkD/3ALDCkPnPRXsKsNQ7i4uiPQVr9OT3N5/FAwAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACskxDtCQAAcDYbMv+5aE/htLyzuCiq358rKAAAwDoECgAAsA6BAgAArNPrgbJ48WK5XC7Nnj3b2Xbs2DGVlZUpLS1N/fv3V3FxsZqamnp7KgAAIEb0aqBs27ZN999/v774xS+Gbb/55pv17LPPat26dXrllVd04MABXX311b05FQAAEEN6LVAOHz6skpISPfjggxo4cKCzPRgM6qGHHtI999yjr33taxo7dqxWr16tv/71r9qyZUtvTQcAAMSQXguUsrIyFRUVqaCgIGx7XV2d2trawrYPHz5c2dnZqqmp6a3pAACAGNIr74Py+OOPa8eOHdq2bdtJ+wKBgBITE5WSkhK23efzKRAIdHq81tZWtba2Ol+HQqGIzhcAANgl4ldQGhsbddNNN2nNmjVKSkqKyDErKyvl9XqdW1ZWVkSOCwAA7BTxQKmrq9PBgwd10UUXKSEhQQkJCXrllVe0bNkyJSQkyOfz6fjx42ppaQm7X1NTk/x+f6fHrKioUDAYdG6NjY2RnjYAALBIxP/EM3HiRL3xxhth266//noNHz5c8+bNU1ZWlvr06aPq6moVFxdLkurr67V//37l5+d3eky32y232x3pqQIAAEtFPFAGDBigUaNGhW3r16+f0tLSnO3Tp09XeXm5UlNT5fF49JOf/ET5+fm6+OKLIz0dAAAQg6LyYYH33nuv4uLiVFxcrNbWVhUWFuq+++6LxlQAAICFXMYYE+1J9FQoFJLX61UwGJTH44n2dAAgZj+xFjiV3vg04578/uazeAAAgHUIFAAAYB0CBQAAWIdAAQAA1iFQAACAdQgUAABgHQIFAABYh0ABAADWIVAAAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHUIFAAAYB0CBQAAWIdAAQAA1iFQAACAdQgUAABgHQIFAABYh0ABAADWIVAAAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHUIFAAAYB0CBQAAWIdAAQAA1iFQAACAdQgUAABgHQIFAABYh0ABAADWIVAAAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHUIFAAAYB0CBQAAWIdAAQAA1iFQAACAdQgUAABgHQIFAABYh0ABAADWIVAAAIB1Ih4olZWV+tKXvqQBAwYoPT1dU6dOVX19fdiYY8eOqaysTGlpaerfv7+Ki4vV1NQU6akAAIAYFfFAeeWVV1RWVqYtW7Zo48aNamtr0xVXXKEjR444Y26++WY9++yzWrdunV555RUdOHBAV199daSnAgAAYlRCpA9YVVUV9vXDDz+s9PR01dXV6bLLLlMwGNRDDz2ktWvX6mtf+5okafXq1RoxYoS2bNmiiy++ONJTAgAAMabXn4MSDAYlSampqZKkuro6tbW1qaCgwBkzfPhwZWdnq6amptNjtLa2KhQKhd0AAMDZK+JXUD6uo6NDs2fP1qWXXqpRo0ZJkgKBgBITE5WSkhI21ufzKRAIdHqcyspK3Xbbbb051Zg3ZP5z0Z5Cj72zuCjaUwAAWKpXr6CUlZVp165devzxx/+n41RUVCgYDDq3xsbGCM0QAADYqNeuoMyaNUsbNmzQ5s2bdc455zjb/X6/jh8/rpaWlrCrKE1NTfL7/Z0ey+12y+1299ZUAQCAZSJ+BcUYo1mzZumpp57Spk2blJOTE7Z/7Nix6tOnj6qrq51t9fX12r9/v/Lz8yM9HQAAEIMifgWlrKxMa9eu1dNPP60BAwY4zyvxer1KTk6W1+vV9OnTVV5ertTUVHk8Hv3kJz9Rfn4+r+ABAACSeiFQVq5cKUm6/PLLw7avXr1a1113nSTp3nvvVVxcnIqLi9Xa2qrCwkLdd999kZ4KAACIUREPFGNMl2OSkpK0YsUKrVixItLfHgAAnAX4LB4AAGAdAgUAAFinV9+oDTjb8IZ4Z0YsrjOAyOIKCgAAsA6BAgAArEOgAAAA6xAoAADAOjxJFjjL8YRTALGIKygAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6/BGbYga3kAMAHAqXEEBAADWIVAAAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHUIFAAAYB3eB6UTvD8HAADRxRUUAABgHQIFAABYh0ABAADWIVAAAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHUIFAAAYB0CBQAAWIdAAQAA1iFQAACAdQgUAABgHQIFAABYh0ABAADWIVAAAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHWiGigrVqzQkCFDlJSUpLy8PG3dujWa0wEAAJaIWqD88Y9/VHl5uW699Vbt2LFDo0ePVmFhoQ4ePBitKQEAAEtELVDuuecezZgxQ9dff71GjhypVatWqW/fvvr9738frSkBAABLJETjmx4/flx1dXWqqKhwtsXFxamgoEA1NTUnjW9tbVVra6vzdTAYlCSFQqFemV9H69FeOS4AALGiN37HfnRMY0yXY6MSKP/5z3/U3t4un88Xtt3n8+nvf//7SeMrKyt12223nbQ9Kyur1+YIAMBnmXdp7x370KFD8nq9nzomKoHSUxUVFSovL3e+7ujoUHNzs9LS0uRyuaI4s7NPKBRSVlaWGhsb5fF4oj2dsxprfeaw1mcOa31mxOo6G2N06NAhZWZmdjk2KoEyaNAgxcfHq6mpKWx7U1OT/H7/SePdbrfcbnfYtpSUlN6c4meex+OJqf/0sYy1PnNY6zOHtT4zYnGdu7py8pGoPEk2MTFRY8eOVXV1tbOto6ND1dXVys/Pj8aUAACARaL2J57y8nKVlpZq3LhxGj9+vJYuXaojR47o+uuvj9aUAACAJaIWKN/+9rf173//WwsXLlQgENCFF16oqqqqk544izPL7Xbr1ltvPelPaog81vrMYa3PHNb6zPgsrLPLdOe1PgAAAGcQn8UDAACsQ6AAAADrECgAAMA6BAoAALAOgRKD3nvvPX33u99VWlqakpOTlZubq+3btzv7r7vuOrlcrrDbpEmTwo7R3NyskpISeTwepaSkaPr06Tp8+HDYmNdff11f/vKXlZSUpKysLC1ZsuSkuaxbt07Dhw9XUlKScnNz9fzzz4ftN8Zo4cKFysjIUHJysgoKCrR3794IrkbvGTJkyEnr6HK5VFZWJkk6duyYysrKlJaWpv79+6u4uPikNx/cv3+/ioqK1LdvX6Wnp2vOnDk6ceJE2JiXX35ZF110kdxut8477zw9/PDDJ81lxYoVGjJkiJKSkpSXl6etW7eG7e/OXGzW1VpffvnlJ+278cYbw47BWnetvb1dCxYsUE5OjpKTkzV06FD96le/CvtclO78zHL+6Fp31ppzdRcMYkpzc7MZPHiwue6660xtba15++23zQsvvGD27dvnjCktLTWTJk0y//rXv5xbc3Nz2HEmTZpkRo8ebbZs2WL+/Oc/m/POO89ce+21zv5gMGh8Pp8pKSkxu3btMo899phJTk42999/vzPmL3/5i4mPjzdLliwxu3fvNrfccovp06ePeeONN5wxixcvNl6v16xfv9689tpr5utf/7rJyckxH374YS+uUmQcPHgwbA03btxoJJmXXnrJGGPMjTfeaLKyskx1dbXZvn27ufjii80ll1zi3P/EiRNm1KhRpqCgwPztb38zzz//vBk0aJCpqKhwxrz99tumb9++pry83OzevdssX77cxMfHm6qqKmfM448/bhITE83vf/978+abb5oZM2aYlJQU09TU5Izpai6262qtv/KVr5gZM2aEjQkGg879WevuWbRokUlLSzMbNmwwDQ0NZt26daZ///7mt7/9rTOmOz+znD+61p215lz96QiUGDNv3jwzYcKETx1TWlpqpkyZcsr9u3fvNpLMtm3bnG1/+tOfjMvlMu+9954xxpj77rvPDBw40LS2toZ97/PPP9/5+pprrjFFRUVhx87LyzM//OEPjTHGdHR0GL/fb3796187+1taWozb7TaPPfZY1w/WMjfddJMZOnSo6ejoMC0tLaZPnz5m3bp1zv49e/YYSaampsYYY8zzzz9v4uLiTCAQcMasXLnSeDweZ13nzp1rLrjggrDv8+1vf9sUFhY6X48fP96UlZU5X7e3t5vMzExTWVlpjDHdmkus+fhaG/PfQLnppptOOZ617p6ioiJzww03hG27+uqrTUlJiTGmez+znD+6p6u1NoZzdVf4E0+MeeaZZzRu3Dh961vfUnp6usaMGaMHH3zwpHEvv/yy0tPTdf755+tHP/qR3n//fWdfTU2NUlJSNG7cOGdbQUGB4uLiVFtb64y57LLLlJiY6IwpLCxUfX29PvjgA2dMQUFB2PctLCxUTU2NJKmhoUGBQCBsjNfrVV5enjMmVhw/flx/+MMfdMMNN8jlcqmurk5tbW1hj2348OHKzs52HltNTY1yc3PD3nywsLBQoVBIb775pjPm09bw+PHjqqurCxsTFxengoICZ0x35hJLPrnWH1mzZo0GDRqkUaNGqaKiQkePHnX2sdbdc8kll6i6ulpvvfWWJOm1117Tq6++qsmTJ0vq3s8s54/u6WqtP8K5+tRi4tOM8f+9/fbbWrlypcrLy/WLX/xC27Zt009/+lMlJiaqtLRUkjRp0iRdffXVysnJ0T/+8Q/94he/0OTJk1VTU6P4+HgFAgGlp6eHHTchIUGpqakKBAKSpEAgoJycnLAxH538A4GABg4cqEAgcNI7//p8vrBjfPx+nY2JFevXr1dLS4uuu+46Sf99bImJiSd9aOUnH39nj/2jfZ82JhQK6cMPP9QHH3yg9vb2Tsf8/e9/7/ZcYskn11qSvvOd72jw4MHKzMzU66+/rnnz5qm+vl5PPvmkJNa6u+bPn69QKKThw4crPj5e7e3tWrRokUpKSiR172eW80f3dLXWEufqrhAoMaajo0Pjxo3TnXfeKUkaM2aMdu3apVWrVjmBMm3aNGd8bm6uvvjFL2ro0KF6+eWXNXHixKjMO9Y99NBDmjx5crc+Ihz/m87WeubMmc6/c3NzlZGRoYkTJ+of//iHhg4dGo1pxqQnnnhCa9as0dq1a3XBBRdo586dmj17tjIzM53zByKjO2vNufrT8SeeGJORkaGRI0eGbRsxYoT2799/yvuce+65GjRokPbt2ydJ8vv9OnjwYNiYEydOqLm5WX6/3xnzyVcmfPR1V2M+vv/j9+tsTCx499139eKLL+oHP/iBs83v9+v48eNqaWkJG/vJx3+6a+jxeJScnKxBgwYpPj6+y3Xuai6xorO17kxeXp4khf2fZq27NmfOHM2fP1/Tpk1Tbm6uvve97+nmm29WZWWlpO79zHL+6J6u1roznKvDESgx5tJLL1V9fX3YtrfeekuDBw8+5X3++c9/6v3331dGRoYkKT8/Xy0tLaqrq3PGbNq0SR0dHc6JPz8/X5s3b1ZbW5szZuPGjTr//PM1cOBAZ0x1dXXY99q4caPy8/MlSTk5OfL7/WFjQqGQamtrnTGxYPXq1UpPT1dRUZGzbezYserTp0/YY6uvr9f+/fudx5afn6833ngj7ASzceNGeTweJzK7WsPExESNHTs2bExHR4eqq6udMd2ZS6zobK07s3PnTkkK+z/NWnft6NGjiosLP+3Hx8ero6NDUvd+Zjl/dE9Xa90ZztWfELWn5+K0bN261SQkJJhFixaZvXv3mjVr1pi+ffuaP/zhD8YYYw4dOmR+/vOfm5qaGtPQ0GBefPFFc9FFF5lhw4aZY8eOOceZNGmSGTNmjKmtrTWvvvqqGTZsWNhL11paWozP5zPf+973zK5du8zjjz9u+vbte9JL1xISEszdd99t9uzZY2699dZOX7qWkpJinn76afP666+bKVOmRP2laz3R3t5usrOzzbx5807ad+ONN5rs7GyzadMms337dpOfn2/y8/Od/R+99PWKK64wO3fuNFVVVeZzn/tcpy99nTNnjtmzZ49ZsWJFpy99dbvd5uGHHza7d+82M2fONCkpKWGvWOlqLrHgVGu9b98+c/vtt5vt27ebhoYG8/TTT5tzzz3XXHbZZc4Y1rp7SktLzec//3nnpa9PPvmkGTRokJk7d64zpjs/s5w/utbVWnOu7hqBEoOeffZZM2rUKON2u83w4cPNAw884Ow7evSoueKKK8znPvc506dPHzN48GAzY8aMsBOsMca8//775tprrzX9+/c3Ho/HXH/99ebQoUNhY1577TUzYcIE43a7zec//3mzePHik+byxBNPmC984QsmMTHRXHDBBea5554L29/R0WEWLFhgfD6fcbvdZuLEiaa+vj6Cq9G7XnjhBSOp0zl/+OGH5sc//rEZOHCg6du3r/nGN75h/vWvf4WNeeedd8zkyZNNcnKyGTRokPnZz35m2trawsa89NJL5sILLzSJiYnm3HPPNatXrz7pey1fvtxkZ2ebxMREM378eLNly5Yez8V2p1rr/fv3m8suu8ykpqYat9ttzjvvPDNnzpyw90ExhrXujlAoZG666SaTnZ1tkpKSzLnnnmt++ctfhr1EtTs/s5w/utbVWnOu7prLmI+9rR0AAIAFeA4KAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOv8PxRmAu9rm1scAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 2 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 2 is 1.02234 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 3 I reco 1.02, as we may lose a little later 1.01\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 3 is 1.01027 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\")\n",
    "#previously, we went from most-used to least-used CCB vtds until each has unit use\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "CCBuse = [0. for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    minCCBuse = float(input(\"enter target CCBuse for CCB \"+str(j)+\" I reco 1.02, as we may lose a little later\"))\n",
    "    postCCBaddPops = list()\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    #ccbNbrSet = set(unitNbrs[unitNo])\n",
    "    #ccbFrac = [-1.*CCBpopFrac[t][j] for t in range(nHDs) ]  # -1 to go from most- to least-used\n",
    "    #idx = np.argsort(ccbFrac)\n",
    "    preCCBpop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in CCBaddCandidates[j]]\n",
    "    idx = np.argsort(preCCBpop)\n",
    "    i = 0\n",
    "    t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "    while CCBuse[j] < minCCBuse  and i < len(CCBaddCandidates[j]) :  #and CCBpopFrac[t][j] > 0:\n",
    "        t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        HDunitList[t].append(unitNo)\n",
    "        postCCBaddPops.append(np.sum([unitPop[u] for u in HDunitList[t] ]))\n",
    "        i +=1\n",
    "    unitUse[unitNo] = CCBuse[j]\n",
    "    print(\"final unit use of CCB\",j, \"is\",r5(CCBuse[j]),\"; here is a histogram of HDpop using this CCB\")\n",
    "    plt.hist(postCCBaddPops)\n",
    "    plt.axvline(aDP,ls=\"--\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "6a7c856e-bd4b-4400-af78-690abc0d16f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After CCB addition, here is the histogram of HD pops relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 1.01503 0.13143\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs) ]\n",
    "print(\"After CCB addition, here is the histogram of HD pops relative to aDP\")\n",
    "plt.hist([HDvPop[t] / aDP for t in range(nHDs) ], bins=20, weights = HDweight, label= \"HDpop / target\" )\n",
    "plt.show()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "743dac78-eb66-4edc-ac3c-a6d634032ba5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 4604 populated HDs out of 4604\n",
      "this will show if we had any duplicated units in HDunitLists\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "populatedTractList = popHDlist.copy()\n",
    "print(\"there are a total of\",len(populatedTractList),\"populated HDs out of\",nHDs)\n",
    "print(\"this will show if we had any duplicated units in HDunitLists\")\n",
    "excess = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    excess[t] = len(HDunitList[t]) - len(set(HDunitList[t]))\n",
    "plt.hist(excess)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "df5d0e4a-5b17-44e3-968a-825123859ad7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDunitList = [list(set(HDunitList[t])) for t in range(nHDs)]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "fe0b5dcb-0495-40e3-b67a-88cffad2a9ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 52\n",
      "working on HD 1400 time is now 91\n",
      "working on HD 2100 time is now 150\n",
      "working on HD 2800 time is now 202\n",
      "working on HD 3500 time is now 272\n",
      "working on HD 4200 time is now 348\n",
      "out of 4604 total HDs, there were 3000.0 contiguous and 1514.0 complement-contiguous HDs\n",
      "1256 HDs had both discontiguity problems, while enclave-only = 1834 and discontig only= 348\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 1604 1834\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "1f8227fa-2059-4552-a0e2-e489ff6fda08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 730895 district pop vs 769364 target\n",
      "we'll also trim any HD with total islands' pop <= 15387\n",
      "working on HD 1\n",
      "working on HD 549\n",
      "working on HD 1081\n",
      "working on HD 1723\n",
      "working on HD 2247\n",
      "working on HD 2950\n",
      "working on HD 3546\n",
      "working on HD 4098\n",
      "working on HD 4596\n",
      "Out of 1604 discontig HDs 243 had discontig HDs.\n",
      "Of these, 0 won't be under 730895 after all minor discontigys were shed, while 243 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "reclassifying HD 1\n",
      "reclassifying HD 1463\n",
      "reclassifying HD 2950\n",
      "reclassifying HD 4402\n",
      "There are 243 HDs still with both discontinuity problems\n",
      "Additionally, 1044 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%200 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for i, t in enumerate(sPgenerator):    \n",
    "    if i%500 == 0:\n",
    "        print(\"reclassifying HD\",t)\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "f3f24800-f7ee-4199-86a2-b2fa306dd21f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lets classify the noncontig by VRA type for badDiscoList and stillHasEnclave\n",
      "VRA,env,other\n",
      "0\n",
      "0\n",
      "243\n",
      "VRA,env,other\n",
      "6\n",
      "4\n",
      "1034\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"lets classify the noncontig by VRA type for badDiscoList and stillHasEnclave\")\n",
    "for LIST in [badDiscoList, stillHasEnclave]:\n",
    "    print(\"VRA,env,other\")\n",
    "    for LHD in [coreVTDs, envelopeVs,HDsToDraw]:\n",
    "        print(len(set(LHD).intersection(set(LIST))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "59784deb-c9cf-4f5a-b0a9-97bd473ae240",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 807832 district pop vs 769364 target\n",
      "working on enclave-y HD 19 . We have evaluated 0 of 2967 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 356 . We have evaluated 100 of 2967 enclavy HDs.Time is now 13\n",
      "working on enclave-y HD 697 . We have evaluated 200 of 2967 enclavy HDs.Time is now 24\n",
      "working on enclave-y HD 1105 . We have evaluated 300 of 2967 enclavy HDs.Time is now 36\n",
      "working on enclave-y HD 1661 . We have evaluated 400 of 2967 enclavy HDs.Time is now 51\n",
      "working on enclave-y HD 1923 . We have evaluated 500 of 2967 enclavy HDs.Time is now 63\n",
      "working on enclave-y HD 2375 . We have evaluated 600 of 2967 enclavy HDs.Time is now 77\n",
      "working on enclave-y HD 2857 . We have evaluated 700 of 2967 enclavy HDs.Time is now 87\n",
      "working on enclave-y HD 3405 . We have evaluated 800 of 2967 enclavy HDs.Time is now 105\n",
      "working on enclave-y HD 4078 . We have evaluated 900 of 2967 enclavy HDs.Time is now 124\n",
      "working on enclave-y HD 4474 . We have evaluated 1000 of 2967 enclavy HDs.Time is now 145\n",
      "Out of 2967 HDs with enclaves 1044 had enclaves.\n",
      "Of these, 876 wouldn't be over 807832 if all enclaves filled, while 168 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(stillHasEnclave):\n",
    "    if iii%100 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(stillHasEnclave),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "85efd74a-5e61-4091-b5a1-d81fa2af494d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lets classify the noncontig by VRA type for badDiscoList (both probs) and cantFill (big enclave)\n",
      "VRA,envelope,other\n",
      "0\n",
      "0\n",
      "243\n",
      "VRA,envelope,other\n",
      "0\n",
      "0\n",
      "168\n"
     ]
    }
   ],
   "source": [
    "print(\"lets classify the noncontig by VRA type for badDiscoList (both probs) and cantFill (big enclave)\")\n",
    "for LIST in [badDiscoList, cantFill]:\n",
    "    print(\"VRA,envelope,other\")\n",
    "    for LHD in [coreVTDs, envelopeVs,HDsToDraw]:\n",
    "        print(len(set(LHD).intersection(set(LIST))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "b5b5e030-9299-4d6b-ab99-720289021598",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "do any of our complement-discontig HDs have a VRA core enclave?\n",
      "checking for coreVRA enclave for HD 132 out of 411\n",
      "checking for coreVRA enclave for HD 2301 out of 411\n",
      "checking for coreVRA enclave for HD 3075 out of 411\n",
      "checking for coreVRA enclave for HD 3540 out of 411\n",
      "checking for coreVRA enclave for HD 3971 out of 411\n",
      "checking for coreVRA enclave for HD 360 out of 411\n",
      "checking for coreVRA enclave for HD 938 out of 411\n",
      "checking for coreVRA enclave for HD 1903 out of 411\n",
      "checking for coreVRA enclave for HD 4453 out of 411\n",
      "there were a total of 105 HDs that have a coreVRA enclave\n"
     ]
    }
   ],
   "source": [
    "hasCoreEnclave = list()\n",
    "print(\"do any of our complement-discontig HDs have a VRA core enclave?\")\n",
    "for i,t in enumerate(badDiscoList + cantFill):\n",
    "    if i%50 == 0:\n",
    "        print(\"checking for coreVRA enclave for HD\",t,\"out of\",len(badDiscoList + cantFill) )\n",
    "    enclaveLists = getEnclaveLists(HDunitList[t],unitNbrs)\n",
    "    for eL in enclaveLists:\n",
    "        if len(coreUset.intersection(set(eL)) )  > 0:\n",
    "            hasCoreEnclave.append(t)\n",
    "            break\n",
    "print(\"there were a total of\",len(hasCoreEnclave),\"HDs that have a coreVRA enclave\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "5ff0113a-17bd-4dfc-82a6-80ef6bf24025",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "of these, 17 are enclaveOnly (are contig)\n"
     ]
    }
   ],
   "source": [
    "print(\"of these,\",len(set(hasCoreEnclave).intersection(set(cantFill))),\"are enclaveOnly (are contig)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "7c14c786-df7c-4a58-ac91-1f9bdd6edb38",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "visualizing a selection of HDs that have a VRA core enclave\n",
      "enclave pop =  710619.0\n",
      "enclave pop =  124\n",
      "the enclaves for HD 4151\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"visualizing a selection of HDs that have a VRA core enclave\")\n",
    "t = list(set(hasCoreEnclave).intersection(set(cantFill)))[14]\n",
    "enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u],0.2)\n",
    "plotPoly(hdCP[t].buffer(0.05))\n",
    "for eL in enclaveLists:\n",
    "    print(\"enclave pop = \",r5(np.sum([unitPop[uu] for uu in eL]) ) )\n",
    "    for uu in eL:\n",
    "        plotPoly(unitGeom[uu])\n",
    "print(\"the enclaves for HD\",t)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "07963dda-8963-4601-9320-e16dca3d01b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01489 0.13151\n",
      "CCB cluster 0 = unit 4019 with pop 161018.0 now has use of 1.0219283359488593\n",
      "CCB cluster 1 = unit 4020 with pop 185562.0 now has use of 1.0236401391863699\n",
      "CCB cluster 2 = unit 4021 with pop 139686.0 now has use of 1.0223377649692218\n",
      "CCB cluster 3 = unit 4022 with pop 25126.0 now has use of 1.00534321118755\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "3109c76f-f32e-4b20-80f0-1d14e3f0e50d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "#HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "efc6250f-4b2b-412e-a2c4-43c21d66932b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 168 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "for t in cantFill:\n",
    "    plotPoly(hdCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "92b9aa2d-3c8c-466b-9ca0-f5ff0cc71cf5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the barredJettisonSet (cannot be shed in below MUSTFREE code) is {4019, 4020, 4021, 4022}\n",
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n",
      "working on avg unit-to-HDcp dist for HD 3200\n",
      "working on avg unit-to-HDcp dist for HD 4000\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set(list())\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u]% 1 > 0.23 and allUnits[u]%1 < 0.27:\n",
    "        barredJettisonSet.add(u)\n",
    "print(\"the barredJettisonSet (cannot be shed in below MUSTFREE code) is\",barredJettisonSet)\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "08e12157-0dc7-4616-825d-47eddbe96adb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([unitUse[u] for u in countyUnitList[114]],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "964802cd-c6c9-4b11-9c6e-101d258f82f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "How tight are our current unit usages in the 3 counties in St L area?\n",
      "unit usages for units in county 91\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit usages for units in county 95\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit usages for units in county 114\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"How tight are our current unit usages in the 3 counties in St L area?\")\n",
    "coreUnitUse, envUnitUse, otherUnitUse = [0.]*nUnits, [0.]*nUnits, [0.]*nUnits\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        if t in coreVTDs:\n",
    "            coreUnitUse[u] += nDistricts * HDweight[t]\n",
    "        elif t in envelopeVs:\n",
    "            envUnitUse[u] += nDistricts * HDweight[t]\n",
    "        else:\n",
    "            otherUnitUse[u] += nDistricts * HDweight[t]\n",
    "for c in [91,95,114]:\n",
    "    print(\"unit usages for units in county\",c)\n",
    "    plt.hist([coreUnitUse[u] for u in countyUnitList[c]],label=\"usage by coreVTDs\",histtype=\"step\",bins=50)\n",
    "    plt.hist([envUnitUse[u] for u in countyUnitList[c]],label=\"usage by envVTDs\",histtype=\"step\",bins=50)\n",
    "    plt.hist([otherUnitUse[u] for u in countyUnitList[c]],label=\"usage by other HDs\",histtype=\"step\",bins=50)\n",
    "    plt.legend()\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "412bb5ab-215e-4193-b5fd-f3f6bc2ea87d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "91\n",
      "0.0018740893888926032\n",
      "0.015263088873390106\n",
      "0.8603236069106015\n",
      "95\n",
      "0.09520799712790727\n",
      "0.3535782998123854\n",
      "0.5867596659989499\n",
      "114\n",
      "0.21042182074710067\n",
      "0.7928521491692895\n",
      "0.013561023715822747\n"
     ]
    }
   ],
   "source": [
    "for c in [91,95,114]:\n",
    "    print(c)\n",
    "    print(np.sum([envUnitUse[u] for u in countyUnitList[c]])/float(len(countyUnitList[c])) )\n",
    "    print(np.sum([coreUnitUse[u] for u in countyUnitList[c]])/float(len(countyUnitList[c])) )\n",
    "    print(np.sum([otherUnitUse[u] for u in countyUnitList[c]])/float(len(countyUnitList[c])) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "a52854b9-e8f2-4366-bd7d-fd2ec6a70234",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 31\n",
      "working on HD 1400 time is now 55\n",
      "working on HD 2100 time is now 95\n",
      "working on HD 2800 time is now 137\n",
      "working on HD 3500 time is now 190\n",
      "working on HD 4200 time is now 250\n",
      "out of 4604 total HDs, there were 4361.0 contiguous and 2393.0 complement-contiguous HDs\n",
      "209 HDs had both discontiguity problems, while enclave-only = 2002 and discontig only= 34\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"updated classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "4637d2ce-a0a4-4d01-9a23-723a855a1fc7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for 655 HD VTDs within coreVTDs ... \n",
      "0 sPg\n",
      "130 eLg\n",
      "0 bothP\n",
      "for 240 HD VTDs within envelopeVs ... \n",
      "0 sPg\n",
      "18 eLg\n",
      "0 bothP\n",
      "for 3709 HD VTDs within other HD centers ... \n",
      "243 sPg\n",
      "1854 eLg\n",
      "209 bothP\n"
     ]
    }
   ],
   "source": [
    "setName = [\"coreVTDs\",\"envelopeVs\",\"other HD centers\"]\n",
    "for jj,SET in enumerate([set(coreVTDs), set(envelopeVs), set(HDsToDraw)]):\n",
    "    print(\"for\",len(SET), \"HD VTDs within\",setName[jj],\"... \")\n",
    "    for i, LIST in enumerate([sPgenerator,eLgenerator,doubleTroubleList]):\n",
    "        NAME = [\"sPg\", \"eLg\",\"bothP\"]\n",
    "        print(len(set(LIST).intersection(SET)), NAME[i] )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6a6ea05-98ed-46c0-86f0-cc89a5f4e25a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#UH OH -- SOMEHOW WE REGRESSED TO EARLIER PROBLEMATIC HDunitLists.  Reason unknown ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "d184a9cd-e3dc-40da-8363-836d08add48f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4128 0.99919 1 201\n",
      "2976 0.9965 3 2117\n",
      "2979 0.99988 1 626\n",
      "3908 1.00026 1 201\n",
      "4230 0.99925 1 17\n",
      "3878 1.00103 1 645\n",
      "3494 0.99908 1 0\n",
      "4202 0.99576 2 1887\n",
      "3882 0.99618 1 626\n",
      "3276 1.00363 1 0\n",
      "3403 1.00062 6 6829\n",
      "3404 1.00471 1 201\n",
      "4147 1.00251 1 2\n",
      "4212 0.99743 6 6829\n",
      "3254 0.99802 3 2117\n",
      "3063 1.00172 1 941.2476033709427\n",
      "3643 0.99952 1 626\n",
      "3839 0.99895 1 941.2476033709427\n"
     ]
    }
   ],
   "source": [
    "WTFlist = set(envelopeVs).intersection(set(eLgenerator))  #why do these still have enclaves??\n",
    "for t in WTFlist:\n",
    "    enclaveLists = enclaveLists = getEnclaveLists(savedHDunitList[t], unitNbrs)\n",
    "    for eL in enclaveLists:\n",
    "        print(t,r5(HDvPop[t]/aDP),len(eL),np.sum([unitPop[u] for u in eL]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "1b03ca8a-1464-4f3b-b7a6-387c7fd68304",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 807832 district pop vs 769364 target\n",
      "working on enclave-y HD 2 . We have evaluated 0 of 0 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 274 . We have evaluated 100 of 0 enclavy HDs.Time is now 11\n",
      "working on enclave-y HD 469 . We have evaluated 200 of 0 enclavy HDs.Time is now 23\n",
      "working on enclave-y HD 725 . We have evaluated 300 of 0 enclavy HDs.Time is now 33\n",
      "working on enclave-y HD 934 . We have evaluated 400 of 0 enclavy HDs.Time is now 42\n",
      "working on enclave-y HD 1122 . We have evaluated 500 of 0 enclavy HDs.Time is now 51\n",
      "working on enclave-y HD 1537 . We have evaluated 600 of 0 enclavy HDs.Time is now 61\n",
      "working on enclave-y HD 1731 . We have evaluated 700 of 0 enclavy HDs.Time is now 70\n",
      "working on enclave-y HD 1908 . We have evaluated 800 of 0 enclavy HDs.Time is now 83\n",
      "working on enclave-y HD 2090 . We have evaluated 900 of 0 enclavy HDs.Time is now 94\n",
      "working on enclave-y HD 2288 . We have evaluated 1000 of 0 enclavy HDs.Time is now 107\n",
      "working on enclave-y HD 2431 . We have evaluated 1100 of 0 enclavy HDs.Time is now 117\n",
      "working on enclave-y HD 2585 . We have evaluated 1200 of 0 enclavy HDs.Time is now 125\n",
      "working on enclave-y HD 2763 . We have evaluated 1300 of 0 enclavy HDs.Time is now 135\n",
      "working on enclave-y HD 2971 . We have evaluated 1400 of 0 enclavy HDs.Time is now 146\n",
      "working on enclave-y HD 3251 . We have evaluated 1500 of 0 enclavy HDs.Time is now 162\n",
      "working on enclave-y HD 3529 . We have evaluated 1600 of 0 enclavy HDs.Time is now 177\n",
      "working on enclave-y HD 3843 . We have evaluated 1700 of 0 enclavy HDs.Time is now 193\n",
      "working on enclave-y HD 4120 . We have evaluated 1800 of 0 enclavy HDs.Time is now 210\n",
      "working on enclave-y HD 4377 . We have evaluated 1900 of 0 enclavy HDs.Time is now 227\n",
      "working on enclave-y HD 4598 . We have evaluated 2000 of 0 enclavy HDs.Time is now 242\n",
      "Out of 2967 HDs with enclaves 2002 had enclaves.\n",
      "Of these, 1596 wouldn't be over 807832 if all enclaves filled, while 406 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### try to rerun CANFILL code\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(eLgenerator):\n",
    "    if iii%100 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(eLgenerator),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "id": "910677a3-50b0-498d-8f63-3bc6b02517b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for 655 HD VTDs within coreVTDs ... \n",
      "130 canFill\n",
      "0 cantFill\n",
      "for 240 HD VTDs within envelopeVs ... \n",
      "18 canFill\n",
      "0 cantFill\n",
      "for 3709 HD VTDs within other HD centers ... \n",
      "1448 canFill\n",
      "406 cantFill\n"
     ]
    }
   ],
   "source": [
    "setName = [\"coreVTDs\",\"envelopeVs\",\"other HD centers\"]\n",
    "for jj,SET in enumerate([set(coreVTDs), set(envelopeVs), set(HDsToDraw)]):\n",
    "    print(\"for\",len(SET), \"HD VTDs within\",setName[jj],\"... \")\n",
    "    for i, LIST in enumerate([canFill, cantFill]):\n",
    "        NAME = [\"canFill\",\"cantFill\"]\n",
    "        print(len(set(LIST).intersection(SET)), NAME[i] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "afe51ed6-8bca-4f77-9f79-ce980254c0bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 12\n",
      "working on HD 1400 time is now 23\n",
      "working on HD 2100 time is now 37\n",
      "working on HD 2800 time is now 50\n",
      "working on HD 3500 time is now 73\n",
      "working on HD 4200 time is now 103\n",
      "out of 4604 total HDs, there were 4361.0 contiguous and 3989.0 complement-contiguous HDs\n",
      "209 HDs had both discontiguity problems, while enclave-only = 406 and discontig only= 34\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"updated classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "c517c3a1-b177-42d3-813e-9a83b1c45429",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for 655 HD VTDs within coreVTDs ... \n",
      "0 discontigOnly\n",
      "0 enclaveOnly\n",
      "0 bothProblems\n",
      "for 240 HD VTDs within envelopeVs ... \n",
      "0 discontigOnly\n",
      "0 enclaveOnly\n",
      "0 bothProblems\n",
      "for 3709 HD VTDs within other HD centers ... \n",
      "243 discontigOnly\n",
      "406 enclaveOnly\n",
      "209 bothProblems\n"
     ]
    }
   ],
   "source": [
    "setName = [\"coreVTDs\",\"envelopeVs\",\"other HD centers\"]\n",
    "for jj,SET in enumerate([set(coreVTDs), set(envelopeVs), set(HDsToDraw)]):\n",
    "    print(\"for\",len(SET), \"HD VTDs within\",setName[jj],\"... \")\n",
    "    for i, LIST in enumerate([sPgenerator,eLgenerator,doubleTroubleList]):\n",
    "        NAME = [\"discontigOnly\",\"enclaveOnly\",\"bothProblems\"]\n",
    "        print(len(set(LIST).intersection(SET)), NAME[i] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "c9471ca9-0997-45d8-b08b-fc762ef1e003",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the contig pops for discontig Us relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "contigHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in sPgenerator + doubleTroubleList:\n",
    "    uCenterDist = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t]]\n",
    "    starterU = HDunitList[t][uCenterDist.index(np.min(uCenterDist))]\n",
    "    contigUs = getContigFromStarter(starterU,HDunitList[t],unitNbrs)\n",
    "    contigHDpop[t] = np.sum([unitPop[u] for u in contigUs] )\n",
    "print(\"here are the contig pops for discontig Us relative to aDP\")\n",
    "plt.hist([contigHDpop[t]/aDP for t in sPgenerator + doubleTroubleList])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "61af829a-1809-4279-bddb-43e1574d5303",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "FAILlist = list()\n",
    "for t in popHDlist:\n",
    "    if contigHDpop[t] < 0.7 * aDP:\n",
    "        FAILlist.append(t)\n",
    "        plotPoly(tractGeom[t])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "d5f3f9f1-e1b4-4bda-92e8-649c5baf3c54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#### print(len(FAILlist),\"major-discont HDs\")\n",
    "n=40\n",
    "for t in FAILlist[n:n+2] :\n",
    "    #plotPoly(MAP)\n",
    "    plotPoly(hdCP[t].buffer(0.1))\n",
    "    uCenterDist = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t]]\n",
    "    starterU = HDunitList[t][uCenterDist.index(np.min(uCenterDist))]\n",
    "    plotPoly(unitCP[starterU].buffer(0.05))\n",
    "    contigUs = getContigFromStarter(starterU,HDunitList[t],unitNbrs)\n",
    "    for u in HDunitList[t]:\n",
    "        if u in contigUs:\n",
    "            plotPoly(unitGeom[u])\n",
    "        else:\n",
    "            plotPoly(unitGeom[u],0.2)\n",
    "    plt.show()\n",
    "    #pause = input(\"hit any key to continue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "f879f7e4-a308-4128-b068-cee2f20780f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "linkSets = [set(), set(), set()]\n",
    "for u in borderSet:\n",
    "    if unitCP[u].x < -94 and unitCP[u].y < 39 and unitCP[u].y > 37 and u not in coreUset:\n",
    "        linkSets[0].add(u)\n",
    "    if unitCP[u].x > -91. and unitCP[u].y < 38.5 and unitCP[u].y > 37 and u not in coreUset:\n",
    "        linkSets[1].add(u)\n",
    "    if unitCP[u].x > -92. and unitCP[u].y < 40 and unitCP[u].y > 38.9 and u not in coreUset:\n",
    "        linkSets[2].add(u)\n",
    "for i,L in enumerate(linkSets):\n",
    "    for u in L:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(i,unitCP[u])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "5dbdc72f-c00e-4ebb-934b-5558175d0edd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying to border-Link 93 badly discontig HDs\n",
      "477 now contig but still has enclave\n",
      "2591 now contig but still has enclave\n",
      "2598 now contig but still has enclave\n",
      "total number of fixedHDs = 44\n"
     ]
    }
   ],
   "source": [
    "hopeToFixHDs = FAILlist.copy()\n",
    "fixedHDs = list()\n",
    "print(\"trying to border-Link\",len(hopeToFixHDs),\"badly discontig HDs\")\n",
    "for t in hopeToFixHDs:\n",
    "    for L in linkSets:\n",
    "        testList = list(set(HDunitList[t]).union(L) ) \n",
    "        unbroken, noEnclave, __, ___ = enclaveCheck(testList, unitNbrs)   \n",
    "        canLink = unbroken\n",
    "        if unbroken and not noEnclave:\n",
    "            print(t,\"now contig but still has enclave\")  #oops, as run 7/7/24, printed ...\"and noEnclave\"\n",
    "        if canLink:\n",
    "            addedList = set(testList).difference( set(HDunitList[t]) )\n",
    "            fixedHDs.append(t)\n",
    "            HDunitList[t] += addedList\n",
    "            break\n",
    "print(\"total number of fixedHDs =\",len(fixedHDs))       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "966403ac-1f27-4532-9eea-f3333af916a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rerunning CANFILL for the newly fixed HDs\n",
      "Now, let's fill in all enclaves that won't put us over 807832 district pop vs 769364 target\n",
      "working on enclave-y HD 155 . We have evaluated 0 of 44 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 3362 . We have evaluated 20 of 44 enclavy HDs.Time is now 5\n",
      "working on enclave-y HD 4207 . We have evaluated 40 of 44 enclavy HDs.Time is now 12\n",
      "Out of 44 HDs with enclaves 41 had enclaves.\n",
      "Of these, 38 wouldn't be over 807832 if all enclaves filled, while 3 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"rerunning CANFILL for the newly fixed HDs\")\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "thisList = fixedHDs.copy()\n",
    "for iii, t in enumerate(thisList):\n",
    "    if iii%20 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(thisList),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(thisList),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "52d20735-157b-4999-9445-2c4b2e0dabeb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 18\n",
      "working on HD 1400 time is now 36\n",
      "working on HD 2100 time is now 57\n",
      "working on HD 2800 time is now 78\n",
      "working on HD 3500 time is now 115\n",
      "working on HD 4200 time is now 162\n",
      "out of 4604 total HDs, there were 4405.0 contiguous and 4021.0 complement-contiguous HDs\n",
      "174 HDs had both discontiguity problems, while enclave-only = 409 and discontig only= 25\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"updated classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "id": "61f9c204-3f9a-4969-923e-64daf764700a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the histograms of the small piece and enclave list lengths, total no = 199 409\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops / aDP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops / aDP\")\n",
    "plt.hist([np.sum([unitPop[u] for u in s])/aDP for s in smallPieceLists],label=\"small piece 1 pop\",bins=40,histtype='step')\n",
    "plt.hist([np.sum([unitPop[u] for u in e])/aDP for e in enclaveLists],label=\"enclave 1 pop\",bins=40,histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "id": "34e3792f-26b6-4522-be6b-0229fa400600",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "one more time - can we correct contiguous but enclavy HDs with small enclave pops\n",
      "Now, let's fill in all enclaves that won't put us over 807832 district pop vs 769364 target\n",
      "working on enclave-y HD 20 . We have evaluated 0 of 409 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 237 . We have evaluated 20 of 409 enclavy HDs.Time is now 5\n",
      "working on enclave-y HD 382 . We have evaluated 40 of 409 enclavy HDs.Time is now 10\n",
      "working on enclave-y HD 441 . We have evaluated 60 of 409 enclavy HDs.Time is now 20\n",
      "working on enclave-y HD 604 . We have evaluated 80 of 409 enclavy HDs.Time is now 25\n",
      "working on enclave-y HD 671 . We have evaluated 100 of 409 enclavy HDs.Time is now 30\n",
      "working on enclave-y HD 880 . We have evaluated 120 of 409 enclavy HDs.Time is now 36\n",
      "working on enclave-y HD 969 . We have evaluated 140 of 409 enclavy HDs.Time is now 42\n",
      "working on enclave-y HD 1104 . We have evaluated 160 of 409 enclavy HDs.Time is now 48\n",
      "working on enclave-y HD 1509 . We have evaluated 180 of 409 enclavy HDs.Time is now 54\n",
      "working on enclave-y HD 1562 . We have evaluated 200 of 409 enclavy HDs.Time is now 61\n",
      "working on enclave-y HD 1743 . We have evaluated 220 of 409 enclavy HDs.Time is now 65\n",
      "working on enclave-y HD 1868 . We have evaluated 240 of 409 enclavy HDs.Time is now 75\n",
      "working on enclave-y HD 1934 . We have evaluated 260 of 409 enclavy HDs.Time is now 77\n",
      "working on enclave-y HD 2056 . We have evaluated 280 of 409 enclavy HDs.Time is now 81\n",
      "working on enclave-y HD 2289 . We have evaluated 300 of 409 enclavy HDs.Time is now 92\n",
      "working on enclave-y HD 2737 . We have evaluated 320 of 409 enclavy HDs.Time is now 101\n",
      "working on enclave-y HD 3337 . We have evaluated 340 of 409 enclavy HDs.Time is now 115\n",
      "working on enclave-y HD 4035 . We have evaluated 360 of 409 enclavy HDs.Time is now 133\n",
      "working on enclave-y HD 4387 . We have evaluated 380 of 409 enclavy HDs.Time is now 151\n",
      "working on enclave-y HD 4507 . We have evaluated 400 of 409 enclavy HDs.Time is now 161\n",
      "Out of 409 HDs with enclaves 409 had enclaves.\n",
      "Of these, 0 wouldn't be over 807832 if all enclaves filled, while 409 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"one more time - can we correct contiguous but enclavy HDs with small enclave pops\")\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "thisList = eLgenerator.copy()\n",
    "for iii, t in enumerate(thisList):\n",
    "    if iii%20 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(thisList),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(thisList),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "id": "5efad7ea-c57f-4495-b28c-dba4d3512d62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above CANFILL operation ...\n",
      "174 HDs now have discontiguity problems, while enclave-only = 409 and discontig only= 25\n",
      "0 problematic core+envelope VTDs\n"
     ]
    }
   ],
   "source": [
    "print(\"after above CANFILL operation ...\")\n",
    "eLgenerator = cantFill.copy()\n",
    "print(len(doubleTroubleList),\"HDs now have discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "print(len(set(coreVTDs+envelopeVs).intersection(set(eLgenerator+doubleTroubleList+sPgenerator))),\"problematic core+envelope VTDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "id": "f20b66ed-f927-4119-bc5d-7993f7cdd292",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enclaveonly, discontigOnly, then both\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"enclaveonly, discontigOnly, then both\")\n",
    "for i,L in enumerate([eLgenerator,set(sPgenerator).difference(set(doubleTroubleList)),doubleTroubleList]):\n",
    "    for t in L:\n",
    "        plotPoly(tractGeom[t],width)\n",
    "    plotPoly(MAP)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "id": "065ca2bb-c562-4bea-a061-398e188b4d2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "readyToMustFreeList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "id": "cd4ed857-e60b-4234-9bd8-e5b6ecaa2442",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run the MUSTFREE CODE\n",
      "this code will solve large enclaves so HD and complement are contiguous for 409 HDs\n",
      "working on HD 20 cantFill 0 of 409 .Time is now 0\n",
      "working on HD 237 cantFill 20 of 409 .Time is now 0\n",
      "working on HD 382 cantFill 40 of 409 .Time is now 1\n",
      "working on HD 441 cantFill 60 of 409 .Time is now 5\n",
      "working on HD 604 cantFill 80 of 409 .Time is now 6\n",
      "working on HD 671 cantFill 100 of 409 .Time is now 6\n",
      "working on HD 880 cantFill 120 of 409 .Time is now 7\n",
      "working on HD 969 cantFill 140 of 409 .Time is now 8\n",
      "working on HD 1104 cantFill 160 of 409 .Time is now 8\n",
      "working on HD 1509 cantFill 180 of 409 .Time is now 10\n",
      "working on HD 1562 cantFill 200 of 409 .Time is now 12\n",
      "working on HD 1743 cantFill 220 of 409 .Time is now 13\n",
      "working on HD 1868 cantFill 240 of 409 .Time is now 15\n",
      "working on HD 1934 cantFill 260 of 409 .Time is now 16\n",
      "working on HD 2056 cantFill 280 of 409 .Time is now 16\n",
      "working on HD 2289 cantFill 300 of 409 .Time is now 21\n",
      "working on HD 2737 cantFill 320 of 409 .Time is now 23\n",
      "working on HD 3337 cantFill 340 of 409 .Time is now 28\n",
      "working on HD 4035 cantFill 360 of 409 .Time is now 35\n",
      "working on HD 4387 cantFill 380 of 409 .Time is now 45\n",
      "working on HD 4507 cantFill 400 of 409 .Time is now 47\n"
     ]
    }
   ],
   "source": [
    "print(\"run the MUSTFREE CODE\")\n",
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "targetList = eLgenerator.copy()\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(targetList),\"HDs\")\n",
    "for iii,t in enumerate(targetList):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(targetList),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "id": "f31ba08f-6187-4c4d-a4f2-1ad27a634694",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.01542 0.12922\n",
      "CCB cluster 0 = unit 4019 with pop 161018.0 now has use of 1.0214851127871347\n",
      "CCB cluster 1 = unit 4020 with pop 185562.0 now has use of 1.021513707829826\n",
      "CCB cluster 2 = unit 4021 with pop 139686.0 now has use of 1.0197252178869152\n",
      "CCB cluster 3 = unit 4022 with pop 25126.0 now has use of 1.103464500635509\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "postMustFreeUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "plt.hist([HDvPop[t] for t in popHDlist] )\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "unitUse = [0.]*nUnits\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "8bf7ef2d-141c-4ced-8e89-e4841d4e867b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 11\n",
      "working on HD 1400 time is now 25\n",
      "working on HD 2100 time is now 41\n",
      "working on HD 2800 time is now 64\n",
      "working on HD 3500 time is now 121\n",
      "working on HD 4200 time is now 186\n",
      "out of 4604 total HDs, there were 4345.0 contiguous and 4417.0 complement-contiguous HDs\n",
      "175 HDs had both discontiguity problems, while enclave-only = 12 and discontig only= 84\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"updated classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "id": "85920a2e-da7f-4816-b81d-b4160046a3b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now for both-problem HDs, how much enclave pop if we reduce to their contiguous pieces?\n",
      "working on HD 152\n",
      "working on HD 2768\n",
      "working on HD 3508\n",
      "working on HD 4034\n",
      "out of 175 HDs with both problems, 69 had too big of enclaves if we reduce to contigUs\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"now for both-problem HDs, how much enclave pop if we reduce to their contiguous pieces?\")\n",
    "ePops, contigPops = [0.]*nHDs, [HDvPop[t] for t in range(nHDs)]\n",
    "stillHasEnclave = list()\n",
    "for i,t in enumerate(doubleTroubleList):\n",
    "    if i%50 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    uCenterDist = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t]]\n",
    "    starterU = HDunitList[t][uCenterDist.index(np.min(uCenterDist))]\n",
    "    #plotPoly(unitCP[starterU].buffer(0.05))\n",
    "    contigUs = getContigFromStarter(starterU,HDunitList[t],unitNbrs)\n",
    "    contigPops[t] = np.sum([unitPop[u] for u in contigUs])    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    for eL in enclaveLists:\n",
    "        ePops[t] += np.sum([unitPop[u] for u in eL])\n",
    "    if ePops[t] < maxNudgeUpPop:\n",
    "        HDunitList[t] = contigUs.copy()\n",
    "        for eL in enclaveLists:\n",
    "            HDunitList[t] += eL\n",
    "    else:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"out of\",len(doubleTroubleList),\"HDs with both problems,\",len(stillHasEnclave),\"had too big of enclaves if we reduce to contigUs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "id": "afad4341-27ae-4be6-998f-53bcee03b29d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after compressing amenable double-troubles to contig pieces, we have the following for cluster usage\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "doubleTroubleList = stillHasEnclave.copy()\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "plt.hist([HDvPop[t] for t in popHDlist] )\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "unitUse = [0.]*nUnits\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after compressing amenable double-troubles to contig pieces, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "id": "a4564cc9-5397-4d2a-8014-ef6f0a4472b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we have a total of 226 stubborn HDs with contiguity problems\n"
     ]
    }
   ],
   "source": [
    "preMustSwellList = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "triageList = list(set(sPgenerator+eLgenerator+doubleTroubleList))\n",
    "listToFix = list()\n",
    "for t in triageList:\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4)\n",
    "    if not (unbroken and noEnclave):\n",
    "        listToFix.append(t)\n",
    "\n",
    "print(\"we have a total of\",len(listToFix),\"stubborn HDs with contiguity problems\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "id": "edd3b36d-9a4d-4ac2-9d54-e8c397554b49",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDdiam = [0.]*nHDs  #about 1 min per 4000 500-unit HDs\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:  #create a crude average diameter = weighted mean distance from each unit to center\n",
    "        HDdiam[t] += unitPop[u]/HDvPop[t] * unitCP[u].distance(hdCP[t])\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "id": "5878a3a1-6856-4383-873a-38e8951436a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDunitList = [preMustSwellList[t].copy() for t in range(nHDs)] #reset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "id": "1a2dafd1-1aa7-4f82-8d65-a06ea82e4ee4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{4019, 4020, 4021, 4022}\n",
      "[3075, 3588, 3589, 3082, 2574, 4111, 3609, 3103, 3106, 2595, 4130, 2597, 3109, 3111, 4131, 4132, 1067, 3115, 3629, 1068, 3632, 1073, 1074, 52, 2100, 2101, 1079, 2102, 3633, 3636, 3137, 3650, 4163, 1608, 1615, 1616, 3150, 3153, 3154, 2133]\n"
     ]
    }
   ],
   "source": [
    "print(CCBset)\n",
    "print(listToFix[0:40])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4815bc48-6d17-4400-9bd8-bdc21f74936d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "id": "7080fa3e-da93-436d-8ed7-0a2e38f95a38",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will now force all in 226 listToFix to be contiguous and nil-enclave\n",
      "Let's first recalc unitUse\n",
      "Strategy:  1 - reduce HD to its primary contiguous piece.\n",
      "  If this is enclavy, fill enclaves if can do under aDP.  If too much enclave pop, remove some border units from this contig piece\n",
      "  If discontig piece not enclavy, simply grow contiguously until fill\n",
      "fixing HD 3075 elapsed sec = 0\n",
      "for HD 3589 we are starting from the home unit 3076 . Working on fixable HD 2\n",
      "for HD 3082 we are starting from the home unit 2569 . Working on fixable HD 3\n",
      "fixing HD 4130 elapsed sec = 695\n",
      "for HD 3629 we are starting from the home unit 3116 . Working on fixable HD 18\n",
      "for HD 1068 we are starting from the home unit 614 . Working on fixable HD 19\n",
      "fixing HD 3632 elapsed sec = 1404\n",
      "for HD 3632 we are starting from the home unit 3119 . Working on fixable HD 20\n",
      "fixing HD 3137 elapsed sec = 1437\n",
      "fixing HD 4186 elapsed sec = 2770\n",
      "fixing HD 3279 elapsed sec = 2832\n",
      "fixing HD 638 elapsed sec = 2860\n",
      "fixing HD 3199 elapsed sec = 2997\n",
      "fixing HD 2723 elapsed sec = 3624\n",
      "fixing HD 3780 elapsed sec = 3741\n",
      "fixing HD 727 elapsed sec = 3888\n",
      "fixing HD 3818 elapsed sec = 3953\n",
      "for HD 1787 we are starting from the home unit 1341 . Working on fixable HD 116\n",
      "for HD 1792 we are starting from the home unit 1347 . Working on fixable HD 117\n",
      "fixing HD 2310 elapsed sec = 4419\n",
      "fixing HD 3866 elapsed sec = 4436\n",
      "for HD 4389 we are starting from the home unit 3886 . Working on fixable HD 137\n",
      "fixing HD 1837 elapsed sec = 5426\n",
      "fixing HD 4415 elapsed sec = 5897\n",
      "for HD 4134 we are starting from the home unit 3621 . Working on fixable HD 151\n",
      "fixing HD 875 elapsed sec = 6003\n",
      "for HD 2928 we are starting from the home unit 2417 . Working on fixable HD 165\n",
      "for HD 2929 we are starting from the home unit 2418 . Working on fixable HD 166\n",
      "fixing HD 382 elapsed sec = 6454\n",
      "fixing HD 1937 elapsed sec = 6464\n",
      "for HD 4001 we are starting from the home unit 3488 . Working on fixable HD 189\n",
      "fixing HD 4006 elapsed sec = 7073\n",
      "fixing HD 958 elapsed sec = 7851\n",
      "fixing HD 3535 elapsed sec = 9711\n",
      "for HD 4051 we are starting from the home unit 3538 . Working on fixable HD 214\n",
      "for HD 3563 we are starting from the home unit 3050 . Working on fixable HD 218\n",
      "fixing HD 3569 elapsed sec = 10358\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'nCanSwell' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[331], line 103\u001b[0m\n\u001b[0;32m    100\u001b[0m     \u001b[38;5;66;03m#HDnAddedUnits[t] = len(addedList)\u001b[39;00m\n\u001b[0;32m    102\u001b[0m badDiscoList \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m enclaveOnly\n\u001b[1;32m--> 103\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwe partially regrew\u001b[39m\u001b[38;5;124m\"\u001b[39m,\u001b[43mnCanSwell\u001b[49m,\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHDs, leaving\u001b[39m\u001b[38;5;124m\"\u001b[39m,\u001b[38;5;28mlen\u001b[39m(badDiscoList),\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mto regrow from scratch\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[1;31mNameError\u001b[0m: name 'nCanSwell' is not defined"
     ]
    }
   ],
   "source": [
    "print(\"we will now force all in\",len(listToFix),\"listToFix to be contiguous and nil-enclave\")\n",
    "print(\"Let's first recalc unitUse\")\n",
    "unitUse = [0.]*nUnits\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "print(\"Strategy:  1 - reduce HD to its primary contiguous piece.\")\n",
    "print(\"  If this is enclavy, fill enclaves if can do under aDP.  If too much enclave pop, remove some border units from this contig piece\")\n",
    "print(\"  If discontig piece not enclavy, simply grow contiguously until fill\")\n",
    "CCBset = set()\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop)\n",
    "for j in range(nCCBs):\n",
    "    CCBset.add( allUnits.index(j+0.25) )\n",
    "    \n",
    "for ijk,t in enumerate(listToFix):\n",
    "    if ijk%10 == 0:\n",
    "        SEC = r3(time.time()-startTime)\n",
    "        print(\"fixing HD\",t,ijk,\"of\",len(listToFix),\"elapsed sec =\",int(SEC) )\n",
    "    uCenterDist = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t]]\n",
    "    starterU = HDunitList[t][uCenterDist.index(np.min(uCenterDist))]\n",
    "    contigUs = getContigFromStarter(starterU,HDunitList[t],unitNbrs)\n",
    "    contigPop = np.sum([unitPop[u] for u in contigUs])\n",
    "    enclaveLists = getEnclaveLists(contigUs,unitNbrs)\n",
    "    ePop = np.sum([np.sum([unitPop[uu] for uu in eL]) for eL in enclaveLists])\n",
    "    shedBorderSet = set()\n",
    "    if ePop < 0.1 * aDP or contigPop + ePop < 1.2 * aDP:\n",
    "        contigList = contigUs.copy()\n",
    "        for eL in enclaveLists:\n",
    "            contigList += eL\n",
    "    else:  #severe enclave.  Jettison all but closest contiguous set of in HD border units, unless ...\n",
    "        #   we have a CCBu, then that is the starter for the contig boundary list we're saving (to not jettison too many CCBus)\n",
    "        contigBorderUs = list(set(contigUs).intersection(borderSet))\n",
    "        if len(contigBorderUs) > 0:\n",
    "            hasCCBu, CCBu = False, -999\n",
    "            CCBsInHD = set(contigBorderUs).intersection(CCBset)\n",
    "            for u in CCBsInHD:\n",
    "                hasCCBu = True  #these will be found in random order\n",
    "                CCBu = u\n",
    "            if hasCCBu:\n",
    "                starterBorderU = CCBu\n",
    "            else:\n",
    "                borderDist = [hdCP[t].distance(unitCP[u]) for u in contigBorderUs]\n",
    "                starterBorderU = borderDist.index(np.min(borderDist))\n",
    "            keptBorderUs = getContigFromStarter(starterBorderU, contigBorderUs, unitNbrs)\n",
    "            shedBorderUset = set(contigBorderUs).difference(set(keptBorderUs))  #this is like a MUSTFREE operation\n",
    "    contigList = list( set(contigList).difference(shedBorderUset) )\n",
    "\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(contigList, unitNbrs,6)\n",
    "    if not (unbroken and noEnclave):  #likely that jettisoning border units created a discontiguity\n",
    "        contigList = [starterU]  #KISS\n",
    "        print(\"for HD\",t,\"we are starting from the home unit\",starterU,\". Working on fixable HD\",ijk)\n",
    "    \n",
    "    contigPop = np.sum([unitPop[u] for u in contigList])\n",
    "    currPoly = hdCP[t]\n",
    "    for u in contigList:\n",
    "        currPoly = currPoly.union(unitCP[u])  #draw a crude 'polygon' = points collection for below distance calc\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigList.copy(), list()\n",
    "    adjoiners = list(set(getAdjoiners(currList, unitNbrs)).difference(coreUset))  #exclude core VRA units\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "        currPoly) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "    stillGoing = True\n",
    "\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap and uu not in coreUset:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                        currPoly) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigList)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigList + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    #HDnAddedUnits[t] = len(addedList)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "id": "02a9fd3e-3c7a-45d3-b7ed-ffad28d9a9ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 5\n",
      "working on HD 1400 time is now 12\n",
      "working on HD 2100 time is now 19\n",
      "working on HD 2800 time is now 27\n",
      "working on HD 3500 time is now 42\n",
      "working on HD 4200 time is now 57\n",
      "out of 4604 total HDs, there were 4604.0 contiguous and 4604.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"updated classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "id": "0141ac7a-0ae9-40f7-bf9b-9503cb773859",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "#optional intermediate save\n",
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"VRAcontigOffPop.csv\" #\"contigUnpatchedB.csv\"  #underPatched\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc310c01-1188-441f-9af3-3344ae04d660",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "id": "cea58fc2-c389-474a-9800-0f4906640a27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n",
      "working on avg unit-to-HDcp dist for HD 3200\n",
      "working on avg unit-to-HDcp dist for HD 4000\n"
     ]
    }
   ],
   "source": [
    "\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7e5bbde-816d-4935-b5b5-c079af02c4d4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a1e7a46c-7767-469d-8e65-494d333ea3a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "offpopHDunitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "id": "0da29b1f-4119-48b3-a3e9-c990baa322be",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now ready to square up pop\n",
      "here is the current unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and the HDvPop histogram ...\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"now ready to square up pop\")\n",
    "HDvPop =    [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs) ]\n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "print(\"here is the current unit use histogram\")\n",
    "plt.hist(unitUse, weights = [unitPop[u]/statePop for u in range(nUnits)],bins=20)\n",
    "plt.show()\n",
    "print(\"and the HDvPop histogram ...\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=50)\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "id": "27b51cd0-8bb6-4b16-bb79-37498e59ce5c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 756 HDs with pop < 765517 to within 882\n",
      "working on squaring up HD 21 time is now 0\n",
      "working on squaring up HD 234 time is now 28\n",
      "working on squaring up HD 440 time is now 52\n",
      "working on squaring up HD 618 time is now 77\n",
      "working on squaring up HD 812 time is now 79\n",
      "working on squaring up HD 1004 time is now 82\n",
      "working on squaring up HD 1477 time is now 91\n",
      "working on squaring up HD 1611 time is now 129\n",
      "working on squaring up HD 1858 time is now 133\n",
      "working on squaring up HD 1912 time is now 143\n",
      "working on squaring up HD 2099 time is now 149\n",
      "working on squaring up HD 2224 time is now 166\n",
      "working on squaring up HD 2409 time is now 169\n",
      "working on squaring up HD 2659 time is now 183\n",
      "working on squaring up HD 2812 time is now 187\n",
      "working on squaring up HD 3073 time is now 215\n",
      "working on squaring up HD 3611 time is now 234\n",
      "working on squaring up HD 4140 time is now 378\n",
      "working on squaring up HD 4505 time is now 405\n",
      "We have addressed underpop in a total of 756 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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5ORnl5eUax1taWpCdnY3Q0FB069YNDz74IOrq6kx5XCIicnHGTpc507SavXl6SLD0PuNqetnStesq/LPwR0d3w2ZMCrj27duH2tpa8VVUVAQAeOihhxAdHa1xrLa2Fi+++CK6deuGSZMmAQCUSiUyMjLQ1taG//3vf9iwYQPWr1+PJUuWiPeorq5GRkYGxo0bh8rKSsydOxdPPPEEvvjiC7HN5s2bkZOTg9zcXFRUVCAhIQHp6ek4f/682GbevHnYvn07PvjgA/z3v//FuXPn8MADD1j0YRERkWsxdrrMmabVHGHi4EismZaE4ICu1et7BHjj348mGbWHo6Xe+qYayz87bOO7OIZEEASzt0CaO3cuduzYgePHj0Mi6fprGDZsGJKSkpCXlwcA+Pzzz3Hvvffi3LlziIiIAACsWbMGCxYswIULF+Dj44MFCxZg586dqKqqEq/z8MMPo6GhAYWFhQCA5ORk3H777Vi1ahUAQKVSITo6Gs888wwWLlyIxsZG9OzZExs3bsTvfvc7AMCRI0cwcOBAlJWVYdSoUUY9n0KhQFBQEBobGyGVSs39mIiIyEGUKgF3/KMU8sYWrXlcErSv6Nu1YLxL53B1Zm4JDKVKwJ6Tl1B26iKA9rywUX1CxcKo2hYfWJuHBDiybBJ8vMzPenLG72+zn6atrQ0FBQXIysrSGmzt378flZWVePzxx8X3ysrKMGTIEDHYAoD09HQoFAocOnRIbJOamqpxrfT0dJSVlYn33b9/v0YbDw8PpKamim3279+P69eva7QZMGAAevXqJbbRprW1FQqFQuNFRESuq+Nmz4YqrbuLwqpa3PGPUjzyzh48u6kSj7yzB3f8oxSFVbUGz/X0kGBMvzD8OX0A/pzeH2PiwsTP5tc9HH1s2n+VALxXdtqm93AEswOubdu2oaGhATNmzNB6PC8vDwMHDsTo0aPF9+RyuUawBUD8WS6X622jUCjQ3NyMixcvQqlUam3T8Ro+Pj4IDg7W2Uab5cuXIygoSHxFR0fr/gCIiMglqAMFfZXWXY1SJaDs5CV8UnkWZScvQalqH3dSj0J1XiigLoFhTNClz8TBkdizaILBjbMtdab+mk2v7whml4XIy8vDpEmTEBUV1eVYc3MzNm7ciMWLF1vUOXtbtGgRcnJyxJ8VCgWDLiIiN2BprSpH6zhFePpiE94vr9EoVhoZ5IfFGQOxbOePNi+B4ePlgZd+OwSzCyrMvoYhvUMCbHZtRzEr4Dpz5gyKi4uxdetWrcc//PBDXLt2DX/4wx803pfJZF1WE6pXDspkMvF/O68mrKurg1Qqhb+/Pzw9PeHp6am1TcdrtLW1oaGhQWOUq2MbbXx9feHr6/ilsUREZH2W1KpyJG1V8juTN7bgjxu/13udjiUwnPlzkACYnhLj6G5YnVlTivn5+QgPD0dGRobW43l5ebjvvvvQs2dPjfdTUlJw8OBBjdWERUVFkEqliI+PF9uUlJRonFdUVISUlBQAgI+PD4YPH67RRqVSoaSkRGwzfPhweHt7a7Q5evQoampqxDZERESm0jWVZyu6pgg7M6UXppTA6Py8bTdU+PbYBTz3wQET7miajKGRFiXMOyuTR7hUKhXy8/ORmZkJL6+up584cQLffPMNPvvssy7H7r77bsTHx2P69On45z//CblcjhdeeAHZ2dniyNLs2bOxatUqPP/888jKykJpaSm2bNmCnTt3itfJyclBZmYmRowYgZEjR2LlypVoamrCzJkzAQBBQUF4/PHHkZOTg5CQEEilUjzzzDNISUkxeoUiERFRR/bej1FflXxLhHUzbiZH2/NKJID5tQ0M8/YAXn94mO1u4EAmh5DFxcWoqalBVlaW1uPr1q3DrbfeirvvvrvLMU9PT+zYsQOenp5ISUnBtGnT8Ic//AF/+9vfxDaxsbHYuXMnioqKkJCQgH/9619Yu3Yt0tPTxTZTp07Fq6++iiVLliAxMRGVlZUoLCzUSKRfsWIF7r33Xjz44IO46667IJPJdE6BEhER6WPrZHRtDFXJN9dzWyoN9lfX89oy2AKA2b/p6zJ5daayqA6Xu3PGOh5ERGRf6lpeuoIfW9Xy+qTyLJ7dVGnWuRLonmZU91DXCk1Dz2us7n5euNJyw3DDDl5/OBFTEm+x6L6Ac35/u98kKRERkRU5aj9GU6vfS9A+xfnvR5MQIdV9rjoQe3H7Ya05aJaOrEkAhAR6mxxsAYDU2+ziCU6PARcREZEejtqPcWRsiNHb6XQs4nrP0Ej866EEve31BYnWeI7fmjlK9Z/vaiy+t7NiwEVERKSHo/Zj1Fclv7PORVwvNrUaOKOdtuDKkucICfTGm9OSkBqvuwSTPj/VN5t9b2fnvmN3REREVqAeaTK0H+PI2BCr31tdJV/b6siHb++FmLAArUVcLQkSDT2vLiEB3tizKBU+Xh5QqgSEBPqgvqnNhCsA3Xw9TWrvShhwERER6aEeaXq6oKJLMro99mM0p0q+JUGivufV5/5ht2D/mcti3+5PjMK63aeNPLvd70fcalJ7V8IpRSIiIgMcvR+jukr+lMRbkNI31GBwZ+ym3QC0FnJNi5fh2Qn9EGDCiNO63ac1NsoO8jd9k+teod1MPsdVsCyEHs64rJSIiByn456GrrAfo65irYszBuL4+Sbk765GQ/N1jWP3JURi83c/o+HadW2XtJkeAd747oU0q3yezvj9zYBLD2f8hRER0c3BWsFd5+tcbmrDX7YdtHtAZUhwgDf2u3HAxRwuIiIiJ6NtZCrY3xszx8Rgzvh+JgUlHTftLqyqxR83Vli9v9bQcO2602+sbQnmcBERETkRXdvqNDRfx4ri4xj+f0Vat+YxtLG2em9GZ2btWmbOhCNcRERETsKYDasbrl3H7IIK/PvRJNwztD1Z35iNtW21N6M1WbuWmTPhCBcREZGTMCUomvN+BT774ZzRG2u7wujRZRPrdrkSBlxEREROwpSgSCUAf9z4PRZuPah1RKzznolh3Xyt0kdb+tuOQ1r3d3QHDLiIiIichDlTavpWG2rsmWiDOKZHgDeC/a2XnSRXtFp9E3BnwRwuIiIiJzG8dw94SNpHr6zJGtOJwQHeeOn+wegR6KtRqgIAVpWewIriYxbfA3CNqU9zMOAiIiJyEvvPXLZ6sAVYnoweEuiDPYsmwMdL+8RYf1k3BAd4W6W2l7smznNKkYiIyElYe3RHgvbViiNjQzC8dw+EBHqbdZ36pjbsP3NZ6zF10r41gq2I7j422QTcGTDgIiIichK2GN3JnRyPosNyjH3lK9Q3mR8UaQsGjSljYQpn3yrJEpxSJCIisgJrbMUzMjYEkUF+kDe2WBzEhAR646XfDgEAPF1QYfH1Ll5phVIlaDyTtWt7fXv8Upd7uAsGXERERBYypvCoMTw9JMidHI+nCyoggWULCxffOwhp8TKMeblU73Wkfl7w9/bE+Sutetst2/kj1u6q1ngma0+BNjS77/Y+nFIkIiKygLGFR401cXAk3pyWBFmQ5vSiTOqLean9MGdcX6OuI5P6YVXpccgV+oMiRcsNNLZcNyq4q21sweyC9oKrgG2mQLlKkYiIiDToy2ES0J60/uL2w0iLl5k0TTZxcCTS4mVapyiVKgEfVZzVOe0oASAL8sPlplasKD5u1P1arquM7hsAzHn/e6yCBOmDZQgJ9EG9FSvEc5UiERERaTCUw6RReNREnh4SpPQNxZTEW5DSN1QM2NTTjkB7cNWR+ufFGfFYtvNHk+9prPYq9xUoOixHYnSQVa7ZcUWlO2LARUREZCZjp7+sPU2mc9oxyA9vTktCj0Afu2xU/eL2w/i+psEq1xIA3JcQ6ZYJ8wCnFImIiMxm7PSXLabJ9E07flJ51ur308baQd3b31RjWK8eJi00cBUMuIiIiMxkqIyDOp/KVtNk6mnHzlw5D8qcnDdXwClFIiIiMxmTT5U7Od7uwYM6EHS1kMWSnDdnx4CLiIjIAobyqRwxPaYvEHQF7lgaglOKREREFtKXT+XIPr05LalLQdYeAd4QAKvsfWgrrjwlqgsDLiIiIivQlU/lSLoCQQDYc+oSZr37Ha61KbWeq84/S4+PwPqyMwbvFezvjYZmy4O4AG9PtywNwYCLiIjIjekKBMfEheG13ydgdkFFl2Pqcbn7EiLxwf6fjbrPG48Mw7G6K/j0wFkc+Flhdn/vGeJ+CfMAIBEEwVqbfLsdhUKBoKAgNDY2QiqVOro7REREVqdrH8j7EiLx9jfVRm350yPAGz6eHqi70mpxf4793yT4eFmWYu6M398c4SIiIrqJaZt2HN67B8a+8pXRm2dftlI+2OShMouDLWfFgIuIiOgm13nasezkJbtUqu8sNV5m93vaCwMuIiIiF6dUCWavkNR2rqPKMpy+2OSQ+9oDAy4iIiIXpisHK3dyvMEaYLrOffj2Xjbrrz7vl9dgzvh+bpk0754TpURERDeBwqpaPF1Q0WX6T97YgqcLKlBYVWvWuSuLjyE4wNvuRVPlila3rDIPmBhwxcTEQCKRdHllZ2eLbcrKyjB+/HgEBgZCKpXirrvuQnNzs3i8oqICaWlpCA4ORmhoKJ588klcvXpVPL5+/Xqt95BIJDh//jwA4Ouvv9Z6XC6Xa/R39erViImJgZ+fH5KTk1FeXm7Wh0RERORslCoBL24/rDWxXf3ei9sPQ6nq2sKYcyUd/tue3LHKPGBiwLVv3z7U1taKr6KiIgDAQw89BKA92Jo4cSLuvvtulJeXY9++fZgzZw48PNpvc+7cOaSmpiIuLg579+5FYWEhDh06hBkzZoj3mDp1qsY9amtrkZ6ejrFjxyI8PFyjP0ePHtVo1/H45s2bkZOTg9zcXFRUVCAhIQHp6eli0EZEROTKyqvr9Sa269uX0JhzL1+7jkBfTyv01DTuWGUeMDGHq2fPnho/v/zyy+jbty/Gjh0LAJg3bx7+9Kc/YeHChWKb/v37i/+9Y8cOeHt7Y/Xq1WIQtmbNGgwdOhQnTpxAXFwc/P394e/vL55z4cIFlJaWIi8vr0t/wsPDERwcrLWvr732GmbNmoWZM2eK99m5cyfWrVun0T8iIiJXZOxIkLZ2xp7b1Kq9Cr2tRAb5uWWVecCCHK62tjYUFBQgKytLnO7bu3cvwsPDMXr0aERERGDs2LHYtWuXeE5rayt8fHzEYAuAGFx1bNfRu+++i4CAAPzud7/rciwxMRGRkZFIS0vD7t27Nfq2f/9+pKam/vqgHh5ITU1FWVmZzmdqbW2FQqHQeBERETkjY0eCwgJ9zT5XF1vltD98ey+3TJgHLAi4tm3bhoaGBnE68NSpUwCApUuXYtasWSgsLERSUhImTJiA48ePAwDGjx8PuVyOV155BW1tbbh8+bI42lRbqz2xLy8vD48++qjGqFdkZCTWrFmDjz76CB999BGio6Pxm9/8BhUV7dsTXLx4EUqlEhERERrXioiI6JLn1dHy5csRFBQkvqKjo837cIiIiGxsZGwIIoP8DCa2P/fBgS7J88aeq4uWtDCrKP5R93e0qzM74MrLy8OkSZMQFRUFAFCpVACAp556CjNnzsSwYcOwYsUK9O/fH+vWrQMADBo0CBs2bMC//vUvBAQEQCaTITY2FhERERqjXmplZWX48ccf8fjjj2u8379/fzz11FMYPnw4Ro8ejXXr1mH06NFYsWKFuY8DAFi0aBEaGxvF108//WTR9YiIiGzF00OC3MnxAKA3cKpTdF2xaOy59nbwrAI7Ks86uhs2YVbAdebMGRQXF+OJJ54Q34uMbK/1ER8fr9F24MCBqKmpEX9+9NFHIZfLcfbsWVy6dAlLly7FhQsX0KdPny73Wbt2LRITEzF8+HCDfRo5ciROnDgBAAgLC4Onpyfq6uo02tTV1UEm013F1tfXF1KpVONFRETkrCYOjsSb05IQIe06baima8Wi+lxZkOb0Ymigjy26arRF2w5qXVnp6swKuPLz8xEeHo6MjAzxvZiYGERFReHo0aMabY8dO4bevXt3uUZERAS6deuGzZs3w8/PD2lpaRrHr169ii1btnQZ3dKlsrJSDPp8fHwwfPhwlJSUiMdVKhVKSkqQkpJi9HMSERE5u4mDI/Gv3yfqbaNrxeLEwZHYtWA83p81Cq8/nIj3Z41C2aIJFk03WupKi9Ita3GZXGlepVIhPz8fmZmZ8PL69XSJRIL58+cjNzcXCQkJSExMxIYNG3DkyBF8+OGHYrtVq1Zh9OjR6NatG4qKijB//ny8/PLLXVYbbt68GTdu3MC0adO69GHlypWIjY3FoEGD0NLSgrVr16K0tBRffvml2CYnJweZmZkYMWIERo4ciZUrV6KpqUlctUhEROQuLl5tNaqdttWJnfdRBIDcyfF4uqDCKn0zhzvW4jI54CouLkZNTQ2ysrK6HJs7dy5aWlowb9481NfXIyEhAUVFRejbt6/Ypry8HLm5ubh69SoGDBiAt956C9OnT+9yrby8PDzwwANayz60tbXhueeew9mzZxEQEIChQ4eiuLgY48aNE9tMnToVFy5cwJIlSyCXy5GYmIjCwsIuifRERESuzthVh8a2mzg4EnNTb8OK4mOWdMts7liLSyIIgvtNlFqJQqFAUFAQGhsbmc9FREROS6kScMc/SiFvbNFaHV4CQBbkh10LxhtdduGTyrN4dlOlNbtplEgT+6mNM35/cy9FIiIiF6dv1aH659zJ8SYFMY4YZZLA9H66CgZcREREbkDXqkNZkB/enJaEiYMjTbqepbW6zPHkXbEm99NVcEpRD2cckiQiItJHqRJQXl2P81daEN69fascc0eMCqtqxeR5ewQLwQHe2P9CmsUjXM74/c0RLiIiIjeiXnU4JfEWpPQNtSh40TVqZisN165jz8lLdrmXvTHgIiIiIp0mDo7E4ox4hNipIGrB3tN2uY+9mVwWgoiIiJyDNacPdSmsqkX2xgq7TCkCwLfHL0GpEtwucZ4BFxERkQsqrKrFi9sPo7bx1yKhkUF+yJ0cj7R4mcFAzJhgTakS8OL2w3YLtgDgausNlFfXdynG6uoYcBEREbkYdTJ750BI3tiC2QUVCA7wRsO16+L76kBMvQJQX7DWcZVgeXW9Rht7ccdK88zhIiIiciH6Rp3U73UMtoD2QOzpggoUVtWKwVrnQKpjGzVHBT7uWGmeI1xEREQuxJxRJwHtRUWXfnoIgERnsCYB8OL2w0iLl8HTQ+KQwKdHgDdGxobY/b62xhEuIiIiF2LuqJMAQK5ohVyh+3wBQG1jC8qr6wE4pvipuxYHZcBFRETkQuwx6qQO6gxtGSQBMOvOWHT3s96EWcO162LA504YcBERETkhpUpA2clL+KTyLMpOtpdKAOwz6tQxqNO3ZdCTd8Vixw+1uNJyw6r3d8ekeeZwERERORlDqwhzJ8fj6YIKSGD8FJwEQITUF4BE77RiZJBflxyqiYMju5SauNzUiuyN39tkCtAdk+Y5wkVEROREjFlFqGvUqUeANwDt038AsPS+QZiSqH9z6PsSIrUWHe24ZdDI2BAs2/mjTYKt7n6ebpk0zxEuIiIiJ2Go5EPHVYTaRp1Gxoag6LC8y+iYrENB1Be3H9bbh08P1OL5iQP1Vnq3ZX2uqcOj3a7KPMCAi4iIyGkYCmTUqwj3nLyEMf3CxFGnjnQFYgCwfne1wUBJvUpRX6V3W+ZYffj9WSzKiHe7oIsBFxERkZMwNpDJ3liBlx8colEVvqPOgZi2nDBT+tF5G6Cwbr5GXcccDdeuiwGlO2HARURE5CSMTRZvaL6Opwsq8Oa0JJ1Bl5qubYCM7Ye2YE0m9UVwgDcar123SR5X2amLbhdwMWmeiIjISZha8uHF7YfFchHamLr5tASaqxR1JfDXKVrR8EuwZYuJP8ENq58y4CIiInISHQuNGtK5Krw2piS3qwOn3Mnt+VPGJPAHB3gj6JeVkdYUHOBj9Ws6GgMuIiIiJ6Iu+RDsb1wgoy/vy5Tk9gipr8YUpTEJ/A3XrnfZKNsaQmwQxDkac7iIiIiczMTBkeju543H1u412LZz3lfHBPeLV1qNvue/fp+IMXG/5k05stp7Q7P1gzhHY8BFRETkhEb1CUVkkB/kjS1ap/UkaK+v1bFIqLYEd2Or0V+8qhmcObLae4gNV0E6CqcUiYiInJChjaOBX/OtAN0J7sbmn4d399PYv1ElCJBJfW26Z6MuMqn7be3DES4iIiInpc7n0lU5Xp1vZepqxI7UI2WXm1pxxz9KNe4THOAtJsjba+FgoA+39iEiIiI701U5vmMldnO32lFf4b6ESK0bUTf+khAfFOBtk+R4ba61KaFUCW5XaZ5TikRERE6u48bRKX1DuwQjxia4d175KAvyw+pHk/DpgVq95R/8vT2R/Zu+5nXeRAKA98pO2+Ve9sQRLiIiIhdnbIL76keT4OEhEUfKhvfugffKThu1f6O8sdns/nX388KVlhtGtz9Tf83sezkrBlxEREQuTl2h3tCKxlEdRscKq2ox9pWvjJ6K/PRArdn96xsWgMqfFUa37x0SYPa9nBWnFImIiFyctVY06nNdzxZChhwwIdiSAJieEmP2vZwVAy4iIiI3oF7RKAvSnF6UBflpVJC3ZEWjObr7eZp0ryfujIGPl/uFJ5xSJCIichMTB0di/IAIvFd2Gmfqr6F3SACmp2gGMOauaDTXrcEB+FF+xai2qQPD8deMQTbukWMw4CIiInIT2irNr91VrVGzy15b9kgkgCDA6GArOaYH1mbebuNeOY77jdkRERG5mY4V4MtOXoJSSz6VrrwseWMLni6oQGFVe9K7rbbsuXdIJOaM64tJg2UA2oMtUzw2srcNeuU8OMJFRETkxLSNWkWaUGleXUvrxe2HkRYvM2pFY49Ab9Q3GVfoVOrnhZcfGIJ7hkZBqRJwxz9KTX1EAMCiTw4iIzHK7Qqeqpk0whUTEwOJRNLllZ2dLbYpKyvD+PHjERgYCKlUirvuugvNzb/W7qioqEBaWhqCg4MRGhqKJ598ElevXtW4j7Z7bNq0SaPN119/jaSkJPj6+iIuLg7r16/v0t/Vq1cjJiYGfn5+SE5ORnl5uSmPS0RE5FDGjloZystS19Iqr643akXj/00ZDJnU8AbSIYHe+O6FNNwzNAptN1RY+mmV2flhTa1KrCo9Yda5rsCkgGvfvn2ora0VX0VFRQCAhx56CEB7sDVx4kTcfffdKC8vx759+zBnzhx4eLTf5ty5c0hNTUVcXBz27t2LwsJCHDp0CDNmzOhyr/z8fI173X///eKx6upqZGRkYNy4caisrMTcuXPxxBNP4IsvvhDbbN68GTk5OcjNzUVFRQUSEhKQnp6O8+fPm/oZERER2Z2hUSugfdRKqRKMzstSt9O1orFHoDeyxsSgR6Avltwbb/B6L/12CHy8PLD8s8MYsPhzvLenxqh+6LJu9ymt06XuQCIIps6y/mru3LnYsWMHjh8/DolEglGjRiEtLQ3Lli3T2v7tt9/G4sWLUVtbKwZhBw8exNChQ3H8+HHExcW1d0oiwccff6wRZHW0YMEC7Ny5E1VVVeJ7Dz/8MBoaGlBYWAgASE5Oxu23345Vq1YBAFQqFaKjo/HMM89g4cKFRj2fQqFAUFAQGhsbIZVKjTqHiIjIGspOXsIj7+wx2O79WaMAwOi2KX1DxZ+VKgHl1fUoOizHtspzqG9qE49FBvnhvoRIbP7u5y77KPYI8MbyB4Zg4uBILP/sMN76ptrYxzK5j+Zwxu9vs5Pm29raUFBQgKysLEgkEpw/fx579+5FeHg4Ro8ejYiICIwdOxa7du0Sz2ltbYWPj48YbAGAv78/AGi0A4Ds7GyEhYVh5MiRWLduHTrGhWVlZUhNTdVon56ejrKyMrFv+/fv12jj4eGB1NRUsY02ra2tUCgUGi8iIiJHMGXUSp2XpSv7SYL2AGpkbIjG+54eEjQ2tyF/92mNYAton7Z8+5tqvHT/EPzn8WTMGdcXc8bF4T9PJOO7F9IwcXAk2m6o8M631gu2AECusF/JCnsyO+Datm0bGhoaxOnAU6dOAQCWLl2KWbNmobCwEElJSZgwYQKOHz8OABg/fjzkcjleeeUVtLW14fLly+JoU23tr1sG/O1vf8OWLVtQVFSEBx98EH/84x/xxhtviMflcjkiIiI0+hMREQGFQoHm5mZcvHgRSqVSaxu5XK7zmZYvX46goCDxFR0dbe7HQ0REZBFjVxOGd/czudK8mjHTlst2HsaovqH4c/oA/Dm9P8bEhYnXea/sNKw9A7j7+AXrXtBJmB1w5eXlYdKkSYiKigLQPmUHAE899RRmzpyJYcOGYcWKFejfvz/WrVsHABg0aBA2bNiAf/3rXwgICIBMJkNsbCwiIiI0Rr0WL16MMWPGYNiwYViwYAGef/55vPLKK5Y8p1EWLVqExsZG8fXTTz/Z/J5ERETamDpqpS8va/Wjw8QVjR2ZkmyvzTc2CI6KDte5ZR6XWQHXmTNnUFxcjCeeeEJ8LzKy/RcZH6+ZZDdw4EDU1PyaRPfoo49CLpfj7NmzuHTpEpYuXYoLFy6gT58+Ou+XnJyMn3/+Ga2trQAAmUyGuro6jTZ1dXWQSqXw9/dHWFgYPD09tbaRyWQ67+Pr6wupVKrxIiIicgRzRq0mDo7E4ox4hAT6iO/VN13Hsp0/iisaOzJ22nL3iYtdaoApVQIqahqMfh5jNbbc0BnguTKzAq78/HyEh4cjIyNDfC8mJgZRUVE4evSoRttjx46hd++uxcwiIiLQrVs3bN68GX5+fkhLS9N5v8rKSvTo0QO+vu1LVFNSUlBSUqLRpqioCCkpKQAAHx8fDB8+XKONSqVCSUmJ2IaIiMjZqUetIjqVaIiQ+mrsj6hWWFWL7I0VWvOxOpaRUDN22nLVVyfw7KZKPPLOHtzxj1IUVtWivLoeV1pumPFUhtmrGr49mVz4VKVSIT8/H5mZmfDy+vV0iUSC+fPnIzc3FwkJCUhMTMSGDRtw5MgRfPjhh2K7VatWYfTo0ejWrRuKioowf/58vPzyywgODgYAbN++HXV1dRg1ahT8/PxQVFSEl156CX/+85/Fa8yePRurVq3C888/j6ysLJSWlmLLli3YuXOn2CYnJweZmZkYMWIERo4ciZUrV6KpqQkzZ84053MiIiJyIF1jXL8ypfipelTMUBFUbdTB28wxMcZ330S2qobvSCYHXMXFxaipqUFWVlaXY3PnzkVLSwvmzZuH+vp6JCQkoKioCH379hXblJeXIzc3F1evXsWAAQPw1ltvYfr06eJxb29vrF69GvPmzYMgCIiLi8Nrr72GWbNmiW1iY2Oxc+dOzJs3D6+//jpuvfVWrF27Funp6WKbqVOn4sKFC1iyZAnkcjkSExNRWFjYJZGeiIjIWakLn3YOhuoU7UFPx1EuU/Kx1GUX1NOWTxdUGN0ndfD2SeU50x7GSN4eki6rKd2BRXW43J0z1vEgIqKbg3qbHF1BlASALMgPuxaMh6eHBJ9UnsWzmyoNXvf1hxMxJfEW8efCqlos3HqwS60tY4SYsAWQKY793yT4eJm/3bMzfn9z82oiIiInZOoKQlPKSKipR9DMCbYAYErCLYYbmeG9stM2ua4jcfNqB1BX9j1/pQXh3duX9LrrZp1ERGQeU1YQnr/SgrBAX8ikfqhT6N6UWtahjIS+nC9jfXLgrAVn63am/ppNrutIDLjszJhd34mIiExZQagWHOAt5lh1DKS0lZEwNIJmDFtMJwJAdA9/m1zXkTilaEfG7vpORERkqPCpNo2/TA0GBXhrvC8L8utSRsKZSy8MkDlH3pU1cYTLTsxZrktERDevjisIO49Y6aL+PvHz8sB/nkjGxautOlNXjB1BCwn06VLXy9bqr9n3fvbAES47sXT7BCIiuvno2q5HHwGAXNEKD4kEUxJvQUrfUK3/R97YrYP2LJqAean9zOq/uViHi8xmyq7vREREahMHRyItXiYutjpedwWrvjpp8DxD3yf6RtA653xt2me/vYWDA7zdsg4XR7jsxJzlukREREB7cJTSNxRTEm/BmLieRp1jzPeJrhG0jjlfe05esji53hQzR8e6ZWoNR7jsxND2CZ2X6xIREWljje+TzuWJ/jt/HPafudylXFFhVS0WfnTQZs/SWXCAN+aMj7Pb/eyJAZedmDJ0S0REpIul3yf6yhN1rkCvbVshW3r5gSFu+z3IKUU7MmboloiIyBBzv0+MLU9kjaKopnrqrli3/h7kXop62GovJlaaJyIiazDl+8SUvRnLq+vxyDt7bNjzriI77AtpKWfcS5FTig6gTn4kIiKyhCnfJ6aUJzJnxbylG1mr7+2u348MuIiIiG4CppQnMnbF/LTkXhjeuwdkQf6QK1owb3OlBT0EvjxU67YBF3O4iIiIbgKmlCe63NRqVNuCvTVYuv0wPtr/E06cv2JJ9wAAH1b8DKXKPTOdOMJFRETk4ozJ5TK2nMTw3j0w9pWvjL53Y/N1fFhx1rIH+MWVFqXbTisy4CIiInJh+so8dFz1Z2w5if1nLtu10GlnRYflbhlwcUqRiIjIRekq81Db2ILZBRV4vfiYxhSdMeUkHL3F3Jbv3HNakSNcRERELsiYWlkrio/j/fKfsPS+X0e7Ou/N2HkK0tFbzF1tvYE9py5hTFyYQ/thbRzhIiIickGGyjyoyRWaRU0Bzb0ZU/qGauR7qXO9HFkdsuzkJQfe3TYYcBEREbkgU6f+Xtx+2KipOnWuFwAHBl3uN6XIgIuIiMgFmTL117GoqTHUuV5BAd5m9s4yKX3cazoRYMBFRETkkob37oGQQB+TzjF1VKzxmvmV480VHOCNUVylSERERI5WWFWLsa98hfqmNpPOM3ZUzBGbV6tNHXGrW+4vzICLiIjIRShVAl4vPobZWkpB6CNBe22ukbEhRrU3NiHfFj49UMuyEEREROQYhVW1WPrpYcgVpgVCHYuaGjty5MhaXO66iTUDLiIiIidXWFWL2QUVZp0r01J13hBH1+JydPFVW2DARURE5MSUKgELtx406Zw54/qiX0R3nfsqGmJo30Vbc3TAZwvM4SIiInJCSpWAspOX8NqXR9Fg4mrBlD5hCO/uh/NX2qfnTM2JcmQtLlNyzVwJR7iIiIicjLYNqY0hARAU4I3nPjigkeulbTNrQ9S1uMzphyVMyTVzJQy4iIiInIh6Q2pzpvIE4JfRMM0RMXlj+/Y+6g2qjdVx30W5ogXLdhxCfZNta3PduKGy6fUdhVOKRERETsKS+lfB/l4I1lEZXn09Y7f36Ui97+Jvh92Cl347xIyemWbRtoNuWRaCARcREZGTMLf+VTdfL7zxSJLeXC9Tt/fRZuLgSDw+Jsbs841xpUVpUR+dFQMuIiIiJ2FuOYRXHxqK+mvGVZ23tORCarzMovON4Y5lIRhwEREROQlTyyHIpL5Y80telrHnWlpyQV0ywpbCAn1ten1HYNI8EZGFlCoB5dX1OH+lxey6R0SAcfWvQgK9sfjeQZBJNf+sXW5qNXh9a5Rc8PSQ4L6ESLz1TbVF19HLDf/6MOAiIrKAtuX75izBJ91upoBWXf/q6YIKSACNoEv9xC/9dkiXP1tKlYBlO380eP3FGYZLLrTdUOG9stM4U38NvUMCMD0lBj5ev06IFVbV4m1bBlsA6hy0j6MtmTSlGBMTA4lE0uWVnZ0ttikrK8P48eMRGBgIqVSKu+66C83NzeLxiooKpKWlITg4GKGhoXjyySdx9epV8fiBAwfwyCOPIDo6Gv7+/hg4cCBef/11jX58/fXXWvshl8s12q1evRoxMTHw8/NDcnIyysvLTfpwiIj0US/f75zkrF6CX1hV66CeuY/Cqlrc8Y9SPPLOHjy7qRKPvLMHd/yj1K0/W3X9K1mnaTtZkJ/Osg7GJtv3CPTRe3z5Z4cxYPHnWLbzR7xbdgbLdv6IAYs/x/LPDgOwbBWlKb7/6bKN72B/Jo1w7du3D0qlUvy5qqoKaWlpeOihhwC0B1sTJ07EokWL8MYbb8DLywsHDhyAh0d7XHfu3DmkpqZi6tSpWLVqFRQKBebOnYsZM2bgww8/BADs378f4eHhKCgoQHR0NP73v//hySefhKenJ+bMmaPRn6NHj0IqlYo/h4eHi/+9efNm5OTkYM2aNUhOTsbKlSuRnp6Oo0eParQjIjKHvi8eAe2jES9uP4y0eJnbjsbYmq56VObWlHIlHetfGTOyZ2ySub52yz87rHWaUCVAfP83/SPsUgTV/YpCmBhw9ezZU+Pnl19+GX379sXYsWMBAPPmzcOf/vQnLFy4UGzTv39/8b937NgBb29vrF69WgzC1qxZg6FDh+LEiROIi4tDVlaWxj369OmDsrIybN26tUvAFR4ejuDgYK19fe211zBr1izMnDlTvM/OnTuxbt06jf4REZnD0IhCxyX4KX1D7dcxN8GA9tf6V8awNGG+7YYK73yrf5rwnW+rcVt4d6PuY6nY0EC73MeezF6l2NbWhoKCAmRlZUEikeD8+fPYu3cvwsPDMXr0aERERGDs2LHYtWuXeE5rayt8fHzEYAsA/P39AUCjXWeNjY0ICema5JeYmIjIyEikpaVh9+7dGn3bv38/UlNTf31QDw+kpqairKxM531aW1uhUCg0XkRE2lhjRIF0MyWgpV+T7XWFnhLoTphXqgQs23EIhmqNqgSg8ucGS7tqkEQCTE+Jsfl97M3sgGvbtm1oaGjAjBkzAACnTp0CACxduhSzZs1CYWEhkpKSMGHCBBw/fhwAMH78eMjlcrzyyitoa2vD5cuXxdGm2lrt8/H/+9//sHnzZjz55JPie5GRkVizZg0++ugjfPTRR4iOjsZvfvMbVFRUAAAuXrwIpVKJiIgIjWtFRER0yfPqaPny5QgKChJf0dHR5n04ROT27LUE/2bFgNY0+jabVv+8OCMe5dX1+KTyLMpOXoJSJYg5cu/tqTHyThK9gZ01TBwk00jSdxdmr1LMy8vDpEmTEBUVBQBQqdr3PnrqqafEabxhw4ahpKQE69atw/LlyzFo0CBs2LABOTk5WLRoETw9PfGnP/0JERERGqNealVVVZgyZQpyc3Nx9913i+/3799fY6py9OjROHnyJFasWIH33nvP3EfCokWLkJOTI/6sUCgYdBGRVoaW70vQnuRs6RL8mxUDWtPp2mxaFuSH+xIisWyn5vvBAd56K9NrExMaoHMVpbUk9ephg6s6nlkB15kzZ1BcXIytW7eK70VGticuxsfHa7QdOHAgamp+jZwfffRRPProo6irq0NgYCAkEglee+019OnTR+O8w4cPY8KECXjyySfxwgsvGOzTyJEjxWnJsLAweHp6oq6uTqNNXV0dZDLdFXJ9fX3h6+t+xdaIyPqMWb6fO9nwEnzSjgGtebQl219uakX2xu+7fI6mBlsAcFt4d4zuF6Y1sLOWny5fs/o1nYFZY3b5+fkIDw9HRkaG+F5MTAyioqJw9OhRjbbHjh1D7969u1wjIiIC3bp1w+bNm+Hn54e0tDTx2KFDhzBu3DhkZmbi73//u1F9qqysFIM+Hx8fDB8+HCUlJeJxlUqFkpISpKSkmPSsRES6mLN8n4xjzBQZA1rt1Mn2UxJvwcjYECzb+aPVRqKm55fjjn+UAgB2LRiP/zyejAAfTytdvV10jwCrXs9ZmDzCpVKpkJ+fj8zMTHh5/Xq6RCLB/PnzkZubi4SEBCQmJmLDhg04cuSIWPIBAFatWoXRo0ejW7duKCoqwvz58/Hyyy+Lqw2rqqowfvx4pKenIycnR8y58vT0FFdJrly5ErGxsRg0aBBaWlqwdu1alJaW4ssvvxTvk5OTg8zMTIwYMQIjR47EypUr0dTUJE53EhFZg6nL98l4+qbIWFjWOOZuhq1P57Icr/0+AbMLKqx2/QER9lkJaW8mB1zFxcWoqanpUr4BAObOnYuWlhbMmzcP9fX1SEhIQFFREfr27Su2KS8vR25uLq5evYoBAwbgrbfewvTp08XjH374IS5cuICCggIUFBSI7/fu3RunT58G0L4K8bnnnsPZs2cREBCAoUOHori4GOPGjRPbT506FRcuXMCSJUsgl8uRmJiIwsLCLon0RESWMmX5PpmGAa1lbLGooHNZjomDIzHrzliDZSWMVd9s3CbcrkYiCII71hezCoVCgaCgIDQ2NmoUWCUiInIFZScv4ZF39tjs+u/PGoWRsSG4/e/FqG+yTqD0n8eTMaZfmEXXcMbvb/dbd0lEREQADNfnstT5Ky1YVXrcasEWANz4peqBu2HARURE5CaUKgFlJy+JtbYA6Fx8YA3Fh+VYUXzcqtfc9v1Zq17PWZhdh4uIiIicR2FVbZcFBpG/LDCwVRmH7T/oLiZurqY2peFGLogjXERERFbSeYRJaWi/HCtRb/TdOaBSrygE2ss4vD9rFFZMTUSPAOcdb7k9hoVPiYiISAd9I0y2LGFhykbf6tW0/t4eVi3lYE2Zo2Md3QWbYMBFRERkIfUIU+egp3PNKnMpVYJYGiOsmy8gABebWhHe3Q8qQTB6o291wDVxcCTWTEvCgo9+QGPzDbP7ZW19ega45T6KAAMuIiIii5gywmRO/TBtI2cdBft7G3WdzjW51DXO3ig5jpUl1k18N9epC9fw2Q/ncM/QKEd3xercM4wkIiKykz0nLxk9wmQqXblZHTU0G7cnoraNvj09JJibdhvWTEtCcIBxgZutvfBJld1y3+yJARcREZGZCqtqkb3RuFwoU6u+6xs5M4UE7blk+jb6njg4EvtfSEP2uL4629hLfdN1s4JTZ8cpRSIiIjPoytvSRdsIkz7W2AfRlI2+PT0k8PG07kbU5rLFlkSOxoCLiIjIRKaMPknQvuG2vhEmbcwJOoL9vTWmGNUbfafFy1B28pLe/SiVKgHvl9eYfE9bCOvm6+guWB0DLiIiIhOZOvpkzAhTZ6aOiAHA6keT4OEh0Qisig7Lccc/Sg2Wqyivrodc4SQjS+6XwsWAi4jIFXQsC6BrhILsx9jRp2B/b7z84BCzSkKo90GUN7YYjD/Uo2ij+oZq/LkwpVyFM03jXWxqdXQXrI4BFxGRk3NUQU3SzdjRp9WPJWFMXJhZ9/D0kCB3cjyeLqiABLoHfXTlaZlarsKcETVbCQt0vylFrlIkInJihrZsKayqdVDPbm7q0SddY4zqlYGj+oRadJ+JgyPx5rQkyIJ0B0OyID+thVUNTXt2Lldh6Jnsyik6YV0c4SIiclK2LqhJ5tM3+mTKykBjqAuU6qo0r2t62dgpQnU7Y0fU7OG8s+SSWREDLiIiJ2XKCIV6yxayH/XoU+fpXpkNpns9PSQm/46NnSLs2E7XM9lbfVObw+5tKwy4iIiclKkjFGR/nUefHLGgQdeCCkNJ97rKVaifac+pS3jyve/Q1Kq0y3N0FMKyEEREZC/mjFCQ/Zkz+mQthhZUmDvt6ekhwZi4MCTHhqD0yAWbPoM2Mqn7/Zlm0jwRkZMyNjHb1IKa5B6MWVChK+leV6J9R0qVgMqfGm3Sd31CA33c8s80R7iIiJyUPROzybWYsqDC3GnP8up6h+RSvTh5kFv+meYIFxGRE7NkhILcl6klH9TTnlMSb0FKp+KoujgqNzC0u/vlbwEc4SIicnrOkJhNzsUeCyoclRtYfFjulqtuGXAREbkARyZmuytX3i7JHgsq1DmE9i4P8XHlWfwlw/2myhlwERGRSzMncHL17ZLMLfmgi67PUJ1DaM8iqPVN192ythwDLiIiclnmBE6mbOhsiKNGyay5oMLQZ/jmtCQs3HoQDdeuW/UZ9HHH2nISQRAcWb3fqSkUCgQFBaGxsRFSqdTR3SEiog50BU7qEENb4KRUCbjjH6U6p8nUI0O7Fox3iVEyS/tQWFWL2QUVXd7v/BkqVQJWlR5H/u7TaGj+NfCKDPLDXycNwMKPq3C19YbFz6P2/qxRFo1wOeP3N0e4iIjI5Zi7z6S1tkuy5iiZJSxZUKFUCVi49aDWY+rPcOmnh9DdzxsXr7ZiRO8QJPXqgb3V9QAEpPQJw6i+ofhn4Y9WDbZYh4uIiMhJmBs4WWN1nzNtKm7JlOaq0hN6pwkFAHJFKx5bu1fr8Y8qzuLeoTK88+1pM3qu25TEKLdLmAcYcBERkQsyN3Cyxuo+Z9lU3JLpRKVKQP7uaovuL29ssXqwBQDj+odb/ZrOgIVPiYjI5ZgbOFljuyRn2FTcmG199CmvrtfIxTKHrRLAj8iv2OjKjsWAi4iIXI65gZN6dZ+6TedzAODh23thxw/nUHbyEpSqrmGFozcVNzSlCbRPaWrru5ozrwL86fI1R3fBJhhwERGRyzEmcNJVFkHXdknBAd4ICvDGiuJjeHZTJR55Zw/u+Edpl9EiR28qbuq2Pto4qoq8MXqHBDi6CzbBgIuIiFySJftMThwciV0LxuP9WaPw+sOJmJfaD5evXe+SRK5tis6SYM8arDGlqQ4anY1EAkxPiXF0N2yCSfNEROSyLCmLoN4uSV2bSxtdqw7VwV7npHWZjepwdVyNeF7RatQ5YYG6N4FWB43aanA5UoC3p1uuUAQYcBERkYuzdJ9Jc1cd2mtTcW2rEY0i0V82YuLgSMxL7YcVxcet2l9LNLUp3XJbH4ABFxER3eSMnaIrPizvEgjYelNxXQVWjZG36xT+/MEBvWUj5ozvh/fLf4Jc4TxJ9PLGZkd3wSZMyuGKiYmBRCLp8srOzhbblJWVYfz48QgMDIRUKsVdd92F5uZfP7yKigqkpaUhODgYoaGhePLJJ3H16lWN+9TU1CAjIwMBAQEIDw/H/PnzceOGZhXbr7/+GklJSfD19UVcXBzWr1/fpb+rV69GTEwM/Pz8kJycjPLyclMel4iIbgLGJpDn7T5tsNyCNelbjWiM0iMXDJaN8PSQYOl98ZCgaz6ao9Q3tTm6CzZhUsC1b98+1NbWiq+ioiIAwEMPPQSgPdiaOHEi7r77bpSXl2Pfvn2YM2cOPDzab3Pu3DmkpqYiLi4Oe/fuRWFhIQ4dOoQZM2aI91AqlcjIyEBbWxv+97//YcOGDVi/fj2WLFkitqmurkZGRgbGjRuHyspKzJ07F0888QS++OILsc3mzZuRk5OD3NxcVFRUICEhAenp6Th//rzZHxYREbkfQ6sOOzJUbsGaDE11mkNb2Qhdiw8CfT2tem9jhXTTnXvmyizavHru3LnYsWMHjh8/DolEglGjRiEtLQ3Lli3T2v7tt9/G4sWLUVtbKwZhBw8exNChQ3H8+HHExcXh888/x7333otz584hIiICALBmzRosWLAAFy5cgI+PDxYsWICdO3eiqqpKvPbDDz+MhoYGFBYWAgCSk5Nx++23Y9WqVQAAlUqF6OhoPPPMM1i4cKFRz+eMm18SEZF59OUz6drEWRtLN1Y21ieVZ/HspkqbXb/zc3T8fMK6+eK5LZWQG5mgb8t+mcMZv7/NLgvR1taGgoICZGVlQSKR4Pz589i7dy/Cw8MxevRoREREYOzYsdi1a5d4TmtrK3x8fMRgCwD8/f0BQGxXVlaGIUOGiMEWAKSnp0OhUODQoUNim9TUVI3+pKeno6ysTOzb/v37Ndp4eHggNTVVbKNNa2srFAqFxouIiFxfYVUt7vhHKR55Z4/WGlsTB0cia0yMUdeyV9FQW9fK6vwc6ny0KYm3wEMiMTvYkgDoEeBt1rmBvp5uuXE1YEHAtW3bNjQ0NIjTgadOnQIALF26FLNmzUJhYSGSkpIwYcIEHD/evgJi/PjxkMvleOWVV9DW1obLly+Lo021te1/6OVyuUawBUD8WS6X622jUCjQ3NyMixcvQqlUam2jvoY2y5cvR1BQkPiKjo4256MhIiInYuw2OGnxMqOuZ6+ioaZMdZpD33NYElQKAKJD/M06t6lViaLDur+nXZnZAVdeXh4mTZqEqKgoAO1TdgDw1FNPYebMmRg2bBhWrFiB/v37Y926dQCAQYMGYcOGDfjXv/6FgIAAyGQyxMbGIiIiQmPUy1EWLVqExsZG8fXTTz85uktERGQBU7bBcXQF+c6MKbBqDmOeQ18NL2P88LN5M0Tqmmf2ypOzJ7OinDNnzqC4uBhPPPGE+F5kZPsS0/j4eI22AwcORE1Njfjzo48+CrlcjrNnz+LSpUtYunQpLly4gD59+gAAZDIZ6urqNK6h/lkmk+ltI5VK4e/vj7CwMHh6empto76GNr6+vpBKpRovIiJyXabU2HJ0BXlt9FXTXzMtCWumJSEk0Mfo6xnzHIVVtXjugwPmdtkixmxL5KrMCrjy8/MRHh6OjIwM8b2YmBhERUXh6NGjGm2PHTuG3r17d7lGREQEunXrhs2bN8PPzw9paWkAgJSUFBw8eFBjNWFRURGkUqkYzKWkpKCkpETjekVFRUhJSQEA+Pj4YPjw4RptVCoVSkpKxDZEROT+TN0Gx5Ltgmyl8zZE788ahV0LxmPi4EhMHByJPYsmICTQuJwpQ8+hnn51dF0uZ95c21wmFz5VqVTIz89HZmYmvLx+PV0ikWD+/PnIzc1FQkICEhMTsWHDBhw5cgQffvih2G7VqlUYPXo0unXrhqKiIsyfPx8vv/wygoODAQB333034uPjMX36dPzzn/+EXC7HCy+8gOzsbPj6tg9xzp49G6tWrcLzzz+PrKwslJaWYsuWLdi5c6d4n5ycHGRmZmLEiBEYOXIkVq5ciaamJsycOdPcz4qIiFyMsflWHdvZq4K8KfQVWPXx8sBLvx2Cp39ZZalrMi4k0AeLMzS3Heq8MnHpp4fMrvtlTc68uba5TA64iouLUVNTg6ysrC7H5s6di5aWFsybNw/19fVISEhAUVER+vbtK7YpLy9Hbm4url69igEDBuCtt97C9OnTxeOenp7YsWMHnn76aaSkpCAwMBCZmZn429/+JraJjY3Fzp07MW/ePLz++uu49dZbsXbtWqSnp4ttpk6digsXLmDJkiWQy+VITExEYWFhl0R6IiJyX+q8LHlji9ZAQoL2UZ/O+Uy2riBvbbr2duzoclMbsjdW4E2P9hEus7cMsjF75snZk0V1uNydM9bxICIi06inyQDN0R/1eJWjpgptoe2GCqOWl+is1q4OMBdnDET2xu+dYjSrszVW+H044/e345cGEhGRW1KqBJSdvIRPKs+i7OQlh608c8a8LFvZf+ay3q1x1EnpL3xS5XTBVqCPp1WCLWfFzauJiMjqtE1Xdd442Z6cMS/LFoxNNq9vum7jnpiuu5+X0bXQXBFHuIiIyKqMLTRqbx0rqaf0DXW7YAtw7WRzuaLVLctBqDHgIiIiqzGl0ChZnzHFW0NNqNtlb+5YDkKNARcREVmNKYVGyfqMKd66bMpgg0GZowb/XHmEzhAGXEREZDWmFhol6zO0SOCeoZF6gzIBgCMGICVoL13hrpg0T0REVmNOoVGyPkOLBHTV7ZIF+WHSYBnW7T5t9z4LgEadMHfDgIuIiKzG3EKjZF2dK8irVAJ2/HBOI/DSFZSVV9c7JOAC2oOuF7cfRlq8zO0WNTDgIiIiq1HnED1dUCFOT6k5agPom42hCvIdy3Noq6ivDpodVYFenePnSpX+jcEcLiIisqqbqdCos9FVkqMjQ+U5OibeO4o75vhxhIuIiKzuZik06kz0leToSED7aKO2qTulSsCek5dQdbYRfcMCcfJiky27rFNIgPOWrjAXAy4iIrIJV9sA2tUZKsnRUcfyHOrfUWFVLRZuPYiGa46vQn9ErsCdt/V0dDesigEXERGRGzBnGk59TmFVLWb/ssG3M/jpcrOju2B1zOEiIiJyA+aU2gjv7gelSsDSTw/ZoEfm6x0S4OguWB0DLiIiIjdgaFufjiRoX62oLgMhV7TauntGkwCYnhLj6G5YHQMuIiK6aShVAspOXsInlWdRdvKSW+3pqG9bn446l+dwthWByX1C4OPlfuEJc7iIiOimoK0+VceaVO5AVwX5jmSdnvm0g1Yi6nJbRHdHd8EmGHAREZHbU9en6jyepa5J5U71wdQlOfacuoSyk5cgQECwvzfCuvlCFuSvUZ5DqRLwfnmNg3usqan1hqO7YBMMuIiIyK3pq0+lryaVK+i4hU/HWmdFh+VdRrlCAr3xf1MGazyjs+VvAcBXRy9AqRJc7ndhCAMuIiJya4bqU2mrSeUKdE2R3pcQibe/qe4SYNY3XccfN36Pp35uwKJ72nO9ig7L7dhj49Q3tbnc78IY7peVRkRE1IGxSeHOljyuj64tfGobW/CWlmCro7e+qcZnP9RCqRKwrfKcbTtqJlf6XRiLI1xEROTWjK1PZU4dK0cwdgsffRZ/UoUgf2/UN7VZrV/W5Cq/C1NwhIuIiNyaofpUHWtSuQJTtvDR5VJTG8pOXbRSj6xL6uflMr8LUzDgIiIit6avPlXnmlS6OEv9LqVKwO4T1gqUnDMp/cHht7pdwjzAKUUiIroJ6KpP1bkmlTbOUr9LWz8sIUBASKA36pscv1l1R8H+Po7ugk1IBEFwnzK7VqZQKBAUFITGxkZIpVJHd4eIiCykq4yCLrrqd6nPsFf9Ll39cEeRQX7YtWC8RaNczvj9zSlFIiK6aXh6SJDSNxRTEm9BSt9Qg9OI+up3Ae31u2w9vWhKkrzkl1dafLhN+2RL6hId7oYBFxERkRam1O9yZD86kgX54c1pSXjnD7fj348mISTQNafnWBaCiIjoJuEs9buMvf6ccX0xL62/OGp3z9BIpA+Woby6HrtPXMSqr07YpH/3Do1EeHdfbPnuZ1y10rY8LAtBRER0k3CW+l3GXn9MXM8uU6TqKdR+Ed3Mvr+hTKqdP9RiWK8e8LJSRMGyEERERDcRZ6nfpe6HIZebdO+JaG5QOC+1HyKkvnrbCAD+tOl7NDRbZ3Tr778d4pZlIRhwERERaWGN+l3W6sfijHiD7Zbt/FFnAr+h4FGb0EAfzBnfD//6faLBttasd5A6MMJ6F3MiDLiIiIh0UNfvknUaYVInp9urDlcPI5LfaxtbsOfkJa3H9AWPutyXEPlLCQ3dI2e28Pedh+16P3thHS49nLGOBxER2Z+p9bus7ZPKs3h2U6XBdsH+3nj5wSE6A0FziqfauzjqoMhu2PnsWIuu4Yzf31ylSEREZIA6+dxRjM3Bami+jqcLKnSOvk0cHIm0+PaVi8WH5fi48qzBYMreleh/vtxs1/vZCwMuIiIiJ6fOwZI3thhVAPXF7YeRFi/TOgqnDh5T+obiLxnxKK+uh1zRgmU7DhkMriSAzavdX2lRQqkS3C5x3qQcrpiYGEgkki6v7OxssU1ZWRnGjx+PwMBASKVS3HXXXWhu/jVaPXbsGKZMmYKwsDBIpVLccccd+Oqrr8Tj69ev13oPiUSC8+fPAwC+/vprrcflcrlGf1evXo2YmBj4+fkhOTkZ5eXlZn1IREREjtQxB8sQYwuydpwmrb/aatRIVqCv7cdpVIDOXDRXZtInt2/fPiiVSvHnqqoqpKWl4aGHHgLQHmxNnDgRixYtwhtvvAEvLy8cOHAAHh6/xnX33nsv+vXrh9LSUvj7+2PlypW49957cfLkSchkMkydOhUTJ07UuO+MGTPQ0tKC8HDNrQqOHj2qMTfb8fjmzZuRk5ODNWvWIDk5GStXrkR6ejqOHj3a5TpERETOTp3Av/Cjg2hoNhwc6SuYau5G2NYqbGpI2amLGNMvzC73sheLkubnzp2LHTt24Pjx45BIJBg1ahTS0tKwbNkyre0vXryInj174ptvvsGdd94JALhy5QqkUimKioqQmpra5ZwLFy7glltuQV5eHqZPnw6gfYRr3LhxuHz5MoKDg7XeKzk5GbfffjtWrVoFAFCpVIiOjsYzzzyDhQsXGvV8zph0R0REN7fdJy7isbV7DbZ7f9YorXlnrrAR9pxxcfhzen+zz3fG72+zy0K0tbWhoKAAWVlZ4nTf3r17ER4ejtGjRyMiIgJjx47Frl27xHNCQ0PRv39/vPvuu2hqasKNGzfw1ltvITw8HMOHD9d6n3fffRcBAQH43e9+1+VYYmIiIiMjkZaWht27d2v0bf/+/RoBnIeHB1JTU1FWVmbuIxMREYmUKgFlJy/hk8qzKDt5yeabWKuN6hNqdkFWUzbCdiRHLlCwFbMnY7dt24aGhgbMmDEDAHDq1CkAwNKlS/Hqq68iMTER7777LiZMmICqqir069cPEokExcXFuP/++9G9e3d4eHggPDwchYWF6NGjh9b75OXl4dFHH4W/v7/4XmRkJNasWYMRI0agtbUVa9euxW9+8xvs3bsXSUlJuHjxIpRKJSIiNIunRURE4MiRIzqfqbW1Fa2tv9YbUSgU5n48ejl6eTEREVlG25RcZJAfcifH27w2lzqf6+mCii5J7IYKspqyEbajeHm0B5XuxuyAKy8vD5MmTUJUVBSA9ik7AHjqqacwc+ZMAMCwYcNQUlKCdevWYfny5RAEAdnZ2QgPD8e3334Lf39/rF27FpMnT8a+ffsQGan5h7SsrAw//vgj3nvvPY33+/fvj/79fx1qHD16NE6ePIkVK1Z0aWuK5cuX48UXXzT7fGM48i8pERFZTteUnLyxRW9JBmtS53N1/j6RGfg+sfVG29YwJfEWtxyEMCvgOnPmDIqLi7F161bxPXWwFB+vuYpi4MCBqKmpAQCUlpZix44duHz5sjin+u9//xtFRUXYsGFDl9yqtWvXIjExUed0Y0cjR44Upy/DwsLg6emJuro6jTZ1dXWQyWQ6r7Fo0SLk5OSIPysUCkRHRxu8t7Gc4S8pERGZT9+UnID2ESZ9JRmsqWNNLWNnTGy90bY1LH9gqKO7YBNm5XDl5+cjPDwcGRkZ4nsxMTGIiorC0aNHNdoeO3YMvXv3BgBcu3at/aYemrf18PAQR8jUrl69ii1btuDxxx83qk+VlZVi0Ofj44Phw4ejpKREPK5SqVBSUoKUlBSd1/D19YVUKtV4WYuhv6RA+19Se+UAEBGR6QxNyRlbksFa1DW1piTegpS+oQaDPHP2VLQnb0+JW45uAWaMcKlUKuTn5yMzMxNeXr+eLpFIMH/+fOTm5iIhIQGJiYnYsGEDjhw5gg8//BAAkJKSgh49eiAzMxNLliyBv78/3nnnHVRXV2sEb0B7WYcbN25g2rRpXfqwcuVKxMbGYtCgQWhpacHatWtRWlqKL7/8UmyTk5ODzMxMjBgxAiNHjsTKlSvR1NQkTnfamyl/Sd0xWZCIyB0YOyXnrFN3+vK/nMF1peC234MmB1zFxcWoqalBVlZWl2Nz585FS0sL5s2bh/r6eiQkJKCoqAh9+/YF0D7VV1hYiL/+9a8YP348rl+/jkGDBuGTTz5BQkKCxrXy8vLwwAMPaC370NbWhueeew5nz55FQEAAhg4diuLiYowbN05sM3XqVFy4cAFLliyBXC5HYmIiCgsLuyTS24ur/yUlIiLjp+SceepOV/6Xs3DX70FuXq2HNet4lJ28hEfe2WOwna66KURE5HhKlYA7/lGqc4sdCdoT13ctGO/0U2NKlYA9py7hyfe+Q1Or0vAJdmKN70G3qsNFpjE0b66vbgoRETmHjlvsdP733FBJBnPZqt6Xp4cEHhKJUwVb7vw9yM2r7cSSuilEROQ8zC3JYA5blxJytum7xRnu+z3IgMuO7PmXlIiIrE9duLr1hgqv/i4BkAAXr7bapIi1PUoJOVuu2fHzVwC453chAy47M6duChEROZ6+0SZr597ao96XUiVAJQgI9vc2ajNse8jffRpzxvdzy+9EBlwOoK6bQkRErsHehattXUpIW/DoDBqar7MsBBER0c3IEdXlTS0lpG2PXgDie2GBvuL05+mL17Cy+JjT1eBSkyucKwi0FgZcREREejiicLWxuVWnL17TOloVHOANAGi45hxThabYffwCfjvsFkd3w+oYcBEREenhiMLV6lJCuup9qa0oPqb1fVcMtNSKDtdBqRLcLo+LdbiIiIj0cER1eXUpIWed9rOlxpYbdtuL0p4YcBEREenhqMLVEwdHYl5qP6te01U4W30wa2DARURkQ7aqEk7244jq8moxYYFWv6YhPX7J/3IkZ6sPZg3M4SIishFbVwkn+3FU4WpHBB6/H3ErbigF5O0+bfd7A+1B7PDePRxyb1vi5tV6OOPml0TkGnTVbVKPgVi7bhNZh7byCh1Hrgwdt0V/9G2WbQuRQX549aEEPLZ2r53u2JWlG1g74/c3R7iIiKzMEXWbyHLGjEjau3C1vn14baW2sQUQ2p/dUYVRmcNFREQGmVK3iZyDekSy8+9NXUm+sKrWQT37dTpTFqQ5vRga6GOze15sakXu5HidCwVsjTlcRERkkCPqNpH5XGFEUts+vMN798DYV76yyXRjeHc/pPQNxZvTkrDgo4NotONeiyGB3lZf8ekMOMJFRGRljqjbROZzlRFJ9XTmlMRbkNI3FD5eHjpXT5qrc4mLiYMjMWdcXytd3ThTEqLccqqdARcRkZU5qm4TmcdVRySVKgHdfb0xaXAEAnw9NY7JpL4IDvA2ORATANwzuH0kTV3CJKybr3U6bKQrLUq73s9eOKVIRGRl+hKdbV23iUzniiOShVW1WLj1YJctfPy9PTB7bBzmjI9D0WG5Scn2HhJAJQB5u08jb/dphAT64P+mDIYsyN8mz6BL0Y9yKFVD3e7vB0e4iIhsQFeisyzIjyUhnIyrjUgWVtVidkGF1v0Sm6+rsKL4GIoOy3X+GdSlc03e+qY2/HFjBUqP1CHSyGtYQ2Oze27twzpcejhjHQ8ici32rttE5lGvUgS0j0g6S5CsVAkY83IJ5IpWve2CA7yx/4U0eHpI0HZDhVHLS1Df1Gb2fWfdGYN3vj1t9vmmWjE1Eb8ddovZ5zvj9zdHuIiIbKhzojODLefkKiOS5dX1BoMtAGi4dh17Tl4CAOw/c9miYAsANu37CX8aF2fRNUxRf9XwM7oa5nARERFBe+kFZxuRNCVxv+zURYzpF2aVZP8rLUq8t/cMggO8tU5lWluIDWuMOQoDLiIiol/Yu5K8qUxL3JeYcY5ulzsEWroS8W+LCMSxuiaL72XvRH174JQiERGRixgZG4JAH+O+utWBo6FFAaYK8PaApNPFPCTAE2NicK7B8tE0Z1qgYE0MuIiIiFyIl6fhr+4eAd4Y1ac94FKXKbGWa9dVXVY0qgRg7e7TuNpqeQ2th2/v5VTTuNbCgIuIiMhFlFfXo7H5hsF2M0bHagQt4qIAqfPUEtPl1mDn76M5GHARERG5CGMT4GPCArq8N3FwJHYvHI95qf2s3S2rqvy5wdFdsAkGXERERC7C0qr4nh4SzBnfD/NS+yHY31vjWGSQH1Y9PMzhKwTdtTooVykSERG5CHUCvLyxResqQQnaa4fpSjovrKrFi9sPa2zWHezvjZljYjFnfBw8PSTw8pJg9i9FYMl6OMJFRETkIjomwHdOKze0T6e6mn7HYAsAGpuvY+Uv2wEpVQKC/H0waXCEDXpvnG5+noYbuSCOcBERkdtyx62V1AnwnUeqZEF+yJ0cr7UqvlIl4MXth7WOigloD9YWbj2IpZ8ehlxheWkHS5y51OzQ+9sKAy4iInJL2qbPIvUEJa7E1Kr45dX1XUa2OhKAXyrI276KvCFfH2kfaXP1wLgzBlxEROR21NNnnUd05I0teLqgwqn2RzRX56r4bTdUWLerGvtOX0KAjxceTLoVo+PC4Okhscr2PvbSfAPYc+oSxsSFOborVsWAi4iI3Iox02cvbj+MtHiZy4+iqKdM1357EqVHLmg887bKcwjw8cRrv0+w2vY+9lJ20v0CLibNExGRWzFm+qy2sQXl1fX265QNFFbV4o5/lOKRd/agpFOwpXatTYnZBRW43NRm1e19bM/9akMw4CIiIrdi7PSZK02zdaZrxaEuf/n4ByzOGAig6+pGZ5Qc67wbiJvLpIArJiYGEomkyys7O1tsU1ZWhvHjxyMwMBBSqRR33XUXmpt/XXFw7NgxTJkyBWFhYZBKpbjjjjvw1VdfadxH2z02bdqk0ebrr79GUlISfH19ERcXh/Xr13fp7+rVqxETEwM/Pz8kJyejvLzclMclIiIXZGlxUGenb8pUl4bmGwgK8MGb05IQIfW1Wd+sxv0GuEwLuPbt24fa2lrxVVRUBAB46KGHALQHWxMnTsTdd9+N8vJy7Nu3D3PmzIGHx6+3uffee3Hjxg2UlpZi//79SEhIwL333gu5XK5xr/z8fI173X///eKx6upqZGRkYNy4caisrMTcuXPxxBNP4IsvvhDbbN68GTk5OcjNzUVFRQUSEhKQnp6O8+fPm/whERGR61AXB9U1kiNB+2pFXcVBnZ2hKVNdyk5egkoloPWGyuRzJw6SdalMb0t7T1+y273sRSII5hfRnzt3Lnbs2IHjx49DIpFg1KhRSEtLw7Jly7S2v3jxInr27IlvvvkGd955JwDgypUrkEqlKCoqQmpqanunJBJ8/PHHGkFWRwsWLMDOnTtRVVUlvvfwww+joaEBhYWFAIDk5GTcfvvtWLVqFQBApVIhOjoazzzzDBYuXGjU8ykUCgQFBaGxsRFSqdSoc4iIyPHUU26A5mCJOghz5VWKn1SexbObKk0+b1h0EL7/qdGse74/axQam9u0rvy0hTnj4vDn9P5mn++M399m53C1tbWhoKAAWVlZkEgkOH/+PPbu3Yvw8HCMHj0aERERGDt2LHbt2iWeExoaiv79++Pdd99FU1MTbty4gbfeegvh4eEYPny4xvWzs7MRFhaGkSNHYt26degYF5aVlYnBmVp6ejrKysrEvu3fv1+jjYeHB1JTU8U22rS2tkKhUGi8iIjI9aiLg8qCNKcNZUF+Lh1sAeZPhZoTbHUcDZw4OBJP3hVr1r1N1bHchbswuyzEtm3b0NDQgBkzZgAATp06BQBYunQpXn31VSQmJuLdd9/FhAkTUFVVhX79+kEikaC4uBj3338/unfvDg8PD4SHh6OwsBA9evQQr/23v/0N48ePR0BAAL788kv88Y9/xNWrV/GnP/0JACCXyxERobntQEREBBQKBZqbm3H58mUolUqtbY4cOaLzmZYvX44XX3zR3I+EiIiciKnFQV2Fof0UtZHA9LSozlsFKVUCNn/3s4lXMZ2flwdG9WHAJcrLy8OkSZMQFRUFoH3KDgCeeuopzJw5EwAwbNgwlJSUYN26dVi+fDkEQUB2djbCw8Px7bffwt/fH2vXrsXkyZOxb98+REa2/z+OxYsXi/cZNmwYmpqa8Morr4gBl60sWrQIOTk54s8KhQLR0dE2vScREdlO5+Kg7kC9n+LTBRVGB1LmTAN23ipoz8lLv1Sjty13CIq1MSvgOnPmDIqLi7F161bxPXWwFB8fr9F24MCBqKmpAQCUlpZix44duHz5sjin+u9//xtFRUXYsGGDztyq5ORkLFu2DK2trfD19YVMJkNdXZ1Gm7q6OkilUvj7+8PT0xOenp5a28hkMp3P5evrC19fF1i9QURENzVd+yl2JpP6ImNIJPJ2nzbquoszBiKsu6/W0cCyUxct7bZReocG2OU+9mZWwJWfn4/w8HBkZGSI78XExCAqKgpHjx7VaHvs2DFMmjQJAHDt2jUA0Fi1qP5ZPUKmTWVlJXr06CEGQykpKfjss8802hQVFSElJQUA4OPjg+HDh6OkpERMvFepVCgpKcGcOXPMeGIiIiLnom3KdHjvHth/5rLGFGp5db1RAVdIoDdmjInVM7pkn1GnmNBAu9zH3kwOuFQqFfLz85GZmQkvr19Pl0gkmD9/PnJzc5GQkIDExERs2LABR44cwYcffgigPVDq0aMHMjMzsWTJEvj7++Odd94RyzwAwPbt21FXV4dRo0bBz88PRUVFeOmll/DnP/9ZvNfs2bOxatUqPP/888jKykJpaSm2bNmCnTt3im1ycnKQmZmJESNGYOTIkVi5ciWamprE6U4iIiJXp23KtPPP6pwvQ6Uk/m/KYL1TeSl9Q7HqqxPmd9YIHhJgekqMTe/hKCYHXMXFxaipqUFWVlaXY3PnzkVLSwvmzZuH+vp6JCQkoKioCH379gUAhIWFobCwEH/9618xfvx4XL9+HYMGDcInn3yChIQEAIC3tzdWr16NefPmQRAExMXF4bXXXsOsWbPE+8TGxmLnzp2YN28eXn/9ddx6661Yu3Yt0tPTxTZTp07FhQsXsGTJEsjlciQmJqKwsLBLIj0REZE765jzpSuX66m7YnHP0Ci91xnVJxTBAd5G53HNHN0bqQNleO6DA5ArjKsbNuvOWPh4uecmOBbV4XJ3zljHg4iIyByFVbVdcr5CA32wbMpg3DPUuDIZhVW1mP1LfTN9/v1oknhNXTXROvKQtAdbi+6J19HCNM74/c2ASw9n/IURERGZS6kSLC6TUVhVi6WfHtY6ahXZaWVjx3M6B3tSPy8M69UDd/ULw/SUGKuObDnj9zcDLj2c8RdGRETkaOrATa5oQf3VVoQE+kAW5K83gLNGsGcsZ/z+NrsOFxEREd2czKlv5o410UzhnplpRERERE6EARcRERGRjTHgIiIiIrIxBlxERERENsaAi4iIiMjGGHARERER2RgDLiIiIiIbY8BFREREZGMMuIiIiIhsjJXm9VDveqRQKBzcEyIiIjKW+nvbmXYvZMClx5UrVwAA0dHRDu4JERERmerSpUsICgpydDcAcPNqvVQqFc6dO4fu3btDIrHNBpu2pFAoEB0djZ9++slpNu+0Jz4/n5/Pz+fn89+cz9/Y2IhevXrh8uXLCA4OdnR3AHCESy8PDw/ceuutju6GxaRS6U35F06Nz8/n5/Pz+W9WN/vze3g4T6q68/SEiIiIyE0x4CIiIiKyMQZcbszX1xe5ubnw9fV1dFccgs/P5+fz8/n5/Hx+Z8GkeSIiIiIb4wgXERERkY0x4CIiIiKyMQZcRERERDbGgIuIiIjIxhhwOdg333yDyZMnIyoqChKJBNu2bdM4LggClixZgsjISPj7+yM1NRXHjx/XaFNfX4/HHnsMUqkUwcHBePzxx3H16lWNNj/88APuvPNO+Pn5ITo6Gv/85z+79OWDDz7AgAED4OfnhyFDhuCzzz4zuS+mWL58OW6//XZ0794d4eHhuP/++3H06FGNNi0tLcjOzkZoaCi6deuGBx98EHV1dRptampqkJGRgYCAAISHh2P+/Pm4ceOGRpuvv/4aSUlJ8PX1RVxcHNavX9+lP6tXr0ZMTAz8/PyQnJyM8vJyk/tiijfffBNDhw4VCxOmpKTg888/vymeXZuXX34ZEokEc+fONem+rvoZLF26FBKJROM1YMCAm+LZ1c6ePYtp06YhNDQU/v7+GDJkCL777jvxuDv/+xcTE9Pl9y+RSJCdnQ3A/X//SqUSixcvRmxsLPz9/dG3b18sW7ZMY+9Dt/v9C+RQn332mfDXv/5V2Lp1qwBA+PjjjzWOv/zyy0JQUJCwbds24cCBA8J9990nxMbGCs3NzWKbiRMnCgkJCcKePXuEb7/9VoiLixMeeeQR8XhjY6MQEREhPPbYY0JVVZXw/vvvC/7+/sJbb70lttm9e7fg6ekp/POf/xQOHz4svPDCC4K3t7dw8OBBk/piivT0dCE/P1+oqqoSKisrhXvuuUfo1auXcPXqVbHN7NmzhejoaKGkpET47rvvhFGjRgmjR48Wj9+4cUMYPHiwkJqaKnz//ffCZ599JoSFhQmLFi0S25w6dUoICAgQcnJyhMOHDwtvvPGG4OnpKRQWFoptNm3aJPj4+Ajr1q0TDh06JMyaNUsIDg4W6urqjO6LqT799FNh586dwrFjx4SjR48Kf/nLXwRvb2+hqqrK7Z+9s/LyciEmJkYYOnSo8Oyzzxp9X1f+DHJzc4VBgwYJtbW14uvChQs3xbMLgiDU19cLvXv3FmbMmCHs3btXOHXqlPDFF18IJ06cENu4879/58+f1/jdFxUVCQCEr776ShAE9//9//3vfxdCQ0OFHTt2CNXV1cIHH3wgdOvWTXj99dfFNu72+2fA5UQ6B1wqlUqQyWTCK6+8Ir7X0NAg+Pr6Cu+//74gCIJw+PBhAYCwb98+sc3nn38uSCQS4ezZs4IgCMK///1voUePHkJra6vYZsGCBUL//v3Fn3//+98LGRkZGv1JTk4WnnrqKaP7Yqnz588LAIT//ve/4vW9vb2FDz74QGzz448/CgCEsrIyQRDaA1YPDw9BLpeLbd58801BKpWKz/v8888LgwYN0rjX1KlThfT0dPHnkSNHCtnZ2eLPSqVSiIqKEpYvX250X6yhR48ewtq1a2+qZ79y5YrQr18/oaioSBg7dqwYcLn7Z5CbmyskJCRoPebuzy4I7f8G3XHHHTqP32z//j377LNC3759BZVKdVP8/jMyMoSsrCyN9x544AHhscceEwTBPX//nFJ0YtXV1ZDL5UhNTRXfCwoKQnJyMsrKygAAZWVlCA4OxogRI8Q2qamp8PDwwN69e8U2d911F3x8fMQ26enpOHr0KC5fviy26XgfdRv1fYzpi6UaGxsBACEhIQCA/fv34/r16xr3HDBgAHr16qXx/EOGDEFERIRGvxUKBQ4dOmTUs7W1tWH//v0abTw8PJCamiq2MaYvllAqldi0aROampqQkpJyUz17dnY2MjIyuvTzZvgMjh8/jqioKPTp0wePPfYYampqbppn//TTTzFixAg89NBDCA8Px7Bhw/DOO++Ix2+mf//a2tpQUFCArKwsSCSSm+L3P3r0aJSUlODYsWMAgAMHDmDXrl2YNGkSAPf8/TPgcmJyuRwANP5CqX9WH5PL5QgPD9c47uXlhZCQEI022q7R8R662nQ8bqgvllCpVJg7dy7GjBmDwYMHi/f08fHpstN7536Z+2wKhQLNzc24ePEilEqlwec31BdzHDx4EN26dYOvry9mz56Njz/+GPHx8TfFswPApk2bUFFRgeXLl3c55u6fQXJyMtavX4/CwkK8+eabqK6uxp133okrV664/bMDwKlTp/Dmm2+iX79++OKLL/D000/jT3/6EzZs2KDxDDfDv3/btm1DQ0MDZsyYId7P3X//CxcuxMMPP4wBAwbA29sbw4YNw9y5c/HYY49pPIM7/f69jG5JZEPZ2dmoqqrCrl27HN0Vu+rfvz8qKyvR2NiIDz/8EJmZmfjvf//r6G7ZxU8//YRnn30WRUVF8PPzc3R37E79/+QBYOjQoUhOTkbv3r2xZcsW+Pv7O7Bn9qFSqTBixAi89NJLAIBhw4ahqqoKa9asQWZmpoN7Z195eXmYNGkSoqKiHN0Vu9myZQv+85//YOPGjRg0aBAqKysxd+5cREVFue3vnyNcTkwmkwFAl9UgdXV14jGZTIbz589rHL9x4wbq6+s12mi7Rsd76GrT8bihvphrzpw52LFjB7766ivceuut4vsymQxtbW1oaGjQ2y9zn00qlcLf3x9hYWHw9PQ0+PyG+mIOHx8fxMXFYfjw4Vi+fDkSEhLw+uuv3xTPvn//fpw/fx5JSUnw8vKCl5cX/vvf/+L//b//By8vL0RERLj9Z9BRcHAwbrvtNpw4ceKm+P1HRkYiPj5e472BAweK06o3y79/Z86cQXFxMZ544gnxvZvh9z9//nxxlGvIkCGYPn065s2bJ452u+PvnwGXE4uNjYVMJkNJSYn4nkKhwN69e5GSkgIASElJQUNDA/bv3y+2KS0thUqlQnJystjmm2++wfXr18U2RUVF6N+/P3r06CG26XgfdRv1fYzpi6kEQcCcOXPw8ccfo7S0FLGxsRrHhw8fDm9vb417Hj16FDU1NRrPf/DgQY2/dEVFRZBKpeI/5oaezcfHB8OHD9doo1KpUFJSIrYxpi/WoFKp0NraelM8+4QJE3Dw4EFUVlaKrxEjRuCxxx4T/9vdP4OOrl69ipMnTyIyMvKm+P2PGTOmSxmYY8eOoXfv3gDc/98/tfz8fISHhyMjI0N872b4/V+7dg0eHpohiKenJ1QqFQA3/f0bnV5PNnHlyhXh+++/F77//nsBgPDaa68J33//vXDmzBlBENqXogYHBwuffPKJ8MMPPwhTpkzRuix22LBhwt69e4Vdu3YJ/fr101gW29DQIERERAjTp08XqqqqhE2bNgkBAQFdlsV6eXkJr776qvDjjz8Kubm5WpfFGuqLKZ5++mkhKChI+PrrrzWWR1+7dk1sM3v2bKFXr15CaWmp8N133wkpKSlCSkqKeFy9NPruu+8WKisrhcLCQqFnz55al0bPnz9f+PHHH4XVq1drXRrt6+srrF+/Xjh8+LDw5JNPCsHBwRorgAz1xVQLFy4U/vvf/wrV1dXCDz/8ICxcuFCQSCTCl19+6fbPrkvHVYru/hk899xzwtdffy1UV1cLu3fvFlJTU4WwsDDh/Pnzbv/sgtBeCsTLy0v4+9//Lhw/flz4z3/+IwQEBAgFBQViG3f+908Q2lcE9urVS1iwYEGXY+7++8/MzBRuueUWsSzE1q1bhbCwMOH5558X27jb758Bl4N99dVXAoAur8zMTEEQ2pejLl68WIiIiBB8fX2FCRMmCEePHtW4xqVLl4RHHnlE6NatmyCVSoWZM2cKV65c0Whz4MAB4Y477hB8fX2FW265RXj55Ze79GXLli3CbbfdJvj4+AiDBg0Sdu7cqXHcmL6YQttzAxDy8/PFNs3NzcIf//hHoUePHkJAQIDw29/+VqitrdW4zunTp4VJkyYJ/v7+QlhYmPDcc88J169f12jz1VdfCYmJiYKPj4/Qp08fjXuovfHGG0KvXr0EHx8fYeTIkcKePXs0jhvTF1NkZWUJvXv3Fnx8fISePXsKEyZMEIMtd392XToHXO78GUydOlWIjIwUfHx8hFtuuUWYOnWqRg0qd352te3btwuDBw8WfH19hQEDBghvv/22xnF3/vdPEAThiy++EABovY67//4VCoXw7LPPCr169RL8/PyEPn36CH/96181yje42+9fIggdyroSERERkdUxh4uIiIjIxhhwEREREdkYAy4iIiIiG2PARURERGRjDLiIiIiIbIwBFxEREZGNMeAiIiIisjEGXEREREQ2xoCLiIiIyMYYcBERERHZGAMuIiIiIhtjwEVERERkY/8fQisi3mHzzp0AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED - here, we've moved to avoidedEnclave and we now disallow picking up VRA coreUs\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList = list()\n",
    "minDistrictPop, maxDistrictPop = 0.995 * aDP, 1.005 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop)\n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) ) \n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%40 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist+coreUs and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = avoidedEnclave(HDunitList[t], unitNbrs, [unitNoToAdd])\n",
    "            #       previously had wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits) \n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist+coreUs and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "id": "bc01409d-d9e4-43a6-9fae-c76aa7bdc855",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "amped unit avg and sd usage are 1.02123 0.12498\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#prevUnitUse = [0.]*nUnits\n",
    "#for t in popHDlist:\n",
    "#    for u in latestHDlist[t]:\n",
    "#        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "#print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "id": "ee512b2b-4daa-4a6b-9452-e8dfdfdebc88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the current barredJettisonSet (usually CCB's) is [4019, 4020, 4021, 4022]\n",
      "4019 0.982487973428707\n",
      "4020 1.0336769991712307\n",
      "4021 0.9944043075832273\n",
      "4022 1.0636744987297142\n"
     ]
    }
   ],
   "source": [
    "#CHECK ON BARRED JETTISON SET BEFORE RUNNING BELOW\n",
    "barredJettisonSet = list()\n",
    "for u in range(nUnits):\n",
    "    if abs(allUnits[u] - int(allUnits[u]) - 0.25) < 0.01:\n",
    "        barredJettisonSet.append(u)\n",
    "print(\"the current barredJettisonSet (usually CCB's) is\",barredJettisonSet)\n",
    "for u in barredJettisonSet:\n",
    "    print(u,unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "id": "5a6cb84c-1d0f-4f02-831c-985fe4078dc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4019, 4020, 4021] {4019, 4020, 4021, 4022}\n"
     ]
    }
   ],
   "source": [
    "origBarredJettisonSet = set(list(barredJettisonSet))\n",
    "for u in origBarredJettisonSet:\n",
    "    if unitUse[u] > 1.04:\n",
    "        barredJettisonSet.remove(u)  #this one is overused in this state\n",
    "print(barredJettisonSet, origBarredJettisonSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "id": "dd7d9818-344c-4150-917b-57a4ee051c92",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 1442 overPopped HDs to within 882\n",
      "working on squaring down HD 0 time is now 0\n",
      "working on squaring down HD 113 time is now 7\n",
      "working on squaring down HD 261 time is now 14\n",
      "working on squaring down HD 374 time is now 19\n",
      "working on squaring down HD 507 time is now 35\n",
      "working on squaring down HD 610 time is now 40\n",
      "working on squaring down HD 742 time is now 46\n",
      "working on squaring down HD 831 time is now 53\n",
      "working on squaring down HD 914 time is now 58\n",
      "working on squaring down HD 1032 time is now 62\n",
      "working on squaring down HD 1125 time is now 77\n",
      "working on squaring down HD 1500 time is now 84\n",
      "working on squaring down HD 1635 time is now 95\n",
      "working on squaring down HD 1720 time is now 100\n",
      "working on squaring down HD 1825 time is now 107\n",
      "working on squaring down HD 1997 time is now 109\n",
      "working on squaring down HD 2096 time is now 113\n",
      "working on squaring down HD 2289 time is now 122\n",
      "working on squaring down HD 2594 time is now 130\n",
      "working on squaring down HD 2776 time is now 136\n",
      "working on squaring down HD 3196 time is now 143\n",
      "working on squaring down HD 3870 time is now 149\n",
      "working on squaring down HD 4357 time is now 155\n",
      "working on squaring down HD 4464 time is now 175\n",
      "working on squaring down HD 4601 time is now 184\n",
      "We have addressed overpop in a total of 1442 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN  #the barred set is dynamic; we stop shedding upon underuse. \n",
    "#   now with avoidedIsland timesaver,  \n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "#HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "#HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "#unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))  \n",
    "barredSet = set(list(barredJettisonSet))\n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    for u in origBarredJettisonSet:\n",
    "        if unitUse[u] < 1.00:\n",
    "            barredSet = barredSet.union({u})  #adding back in when become underused (new for VA)\n",
    "    if ii%60 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "        #barredSet = barredJettisonSet  #see above for VA-on modification\n",
    "        #barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)  #weaker specification - must be close to be barred\n",
    "\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                contig = avoidedIsland(tryList, unitNbrs, [unitNoToShed] )  #new for MO - faster contig check\n",
    "                #unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                #if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                if contig:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                      u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )\n",
    "\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "id": "9a19b23e-43cc-4609-9ee7-6d1057a7a9e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the stats prior to any equi-pop patching\n",
      "amped unit avg and sd usage are 1.02123 0.12498\n",
      "shed unit avg and sd usage are 1.00013 0.11441\n"
     ]
    },
    {
     "data": {
      "image/png": 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m4MCBDd6jblvPnj2Vm5vb4n5a6qW+NWvWaPXq1S58JwAAQFfg1hmhHTt26E9/+pNeeuklffTRR3rhhRf0+OOP64UXXmiv/rxq2bJlKioqcjyys7N93RIAAGhHbp0Ruvfee7V06VLdfPPNkqRRo0bp3//+t9asWaNZs2Y5lhzPy8tTv379HK/Ly8vTmDFjJNUuS15/SfJz587p22+/dbw+KipKeXl5TjV1X7dUc/72lnqpz2KxyGKxuPbNAAAAnZ5bZ4TKysoaLGcdEBAgu90uSRo4cKCioqKUlpbm2F5cXKwDBw4oISFBkpSQkKDCwkJlZGQ4at5++23Z7XbFx8c7avbt2+e0bPnu3bs1dOhQ9ezZ01Fz/n7qaur240ovAADA3NwKQtddd51+85vfKDU1VV9//bVeffVVPfHEE7r++usl1d57ZdGiRXrooYf02muv6dChQ7rtttsUHR2tKVOmSJIuueQSXXvttZo3b54OHjyo9957TwsWLNDNN9+s6OhoSdItt9yioKAgzZ07V4cPH9b27du1fv16paSkOHpZuHChdu3apbVr1+qLL77QqlWr9OGHH2rBggUu9wIAAEzOneloxcXFxsKFC43+/fsbwcHBxkUXXWTcd999TtPc7Xa7cf/99xt9+/Y1LBaLcfXVVxtHjx51ep8zZ84Y06dPN0JDQw2bzWbMnj3bOHv2rFPNJ598YlxxxRWGxWIxYmJijN/+9rcN+tmxY4cxZMgQIygoyBgxYoSRmprqtN2VXprD9HnAs5g+D8Ab3Pn89jOM85aFhpPi4mKFhYWpqKhINpvN1+0And5nOUX61TMvKtVyn3THXil6TKtqAKA57nx+c68xAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWgQhAABgWm4HoZycHN16662KiIiQ1WrVqFGj9OGHHzq2G4ahFStWqF+/frJarUpMTNSXX37p9B7ffvutZsyYIZvNpvDwcM2dO1clJSVONZ9++qmuvPJKBQcHKzY2Vo8++miDXnbu3Klhw4YpODhYo0aN0htvvOG03ZVeAACAebkVhAoKCjRhwgQFBgbq73//uz7//HOtXbtWPXv2dNQ8+uijeuqpp7Rp0yYdOHBA3bt3V1JSkioqKhw1M2bM0OHDh7V79269/vrr2rdvn+644w7H9uLiYl1zzTUaMGCAMjIy9Nhjj2nVqlXavHmzo2b//v2aPn265s6dq48//lhTpkzRlClT9Nlnn7nVCwAAMDHDDb/61a+MK664osntdrvdiIqKMh577DHHc4WFhYbFYjFefvllwzAM4/PPPzckGR988IGj5u9//7vh5+dn5OTkGIZhGM8++6zRs2dPo7Ky0mnfQ4cOdXx90003GZMnT3baf3x8vPGLX/zC5V5aUlRUZEgyioqKXKoH0LxD/yk0frL0acNYaTOMnI9bXQMAzXHn89utM0Kvvfaaxo8frxtvvFGRkZEaO3astmzZ4th+/Phx5ebmKjEx0fFcWFiY4uPjlZ6eLklKT09XeHi4xo8f76hJTEyUv7+/Dhw44Ki56qqrFBQU5KhJSkrS0aNHVVBQ4Kg5fz91NXX7caWX+iorK1VcXOz0AAAAXZdbQeirr77Sxo0bNXjwYL355pu68847ddddd+mFF16QJOXm5kqS+vbt6/S6vn37Orbl5uYqMjLSaXu3bt3Uq1cvp5rG3uP8fTRVc/72lnqpb82aNQoLC3M8YmNjW/qWAACATsytIGS323XZZZfp4Ycf1tixY3XHHXdo3rx52rRpU3v151XLli1TUVGR45Gdne3rlgAAQDtyKwj169dPw4cPd3rukksu0YkTJyRJUVFRkqS8vDynmry8PMe2qKgo5efnO20/d+6cvv32W6eaxt7j/H00VXP+9pZ6qc9ischmszk9AABA1+VWEJowYYKOHj3q9NyxY8c0YMAASdLAgQMVFRWltLQ0x/bi4mIdOHBACQkJkqSEhAQVFhYqIyPDUfP222/LbrcrPj7eUbNv3z5VV1c7anbv3q2hQ4c6ZqglJCQ47aeupm4/rvQCAADMza0gtHjxYr3//vt6+OGHlZWVpZdeekmbN29WcnKyJMnPz0+LFi3SQw89pNdee02HDh3SbbfdpujoaE2ZMkVS7Rmka6+9VvPmzdPBgwf13nvvacGCBbr55psVHR0tSbrlllsUFBSkuXPn6vDhw9q+fbvWr1+vlJQURy8LFy7Url27tHbtWn3xxRdatWqVPvzwQy1YsMDlXgAAgMm5OyXtb3/7mzFy5EjDYrEYw4YNMzZv3uy03W63G/fff7/Rt29fw2KxGFdffbVx9OhRp5ozZ84Y06dPN0JDQw2bzWbMnj3bOHv2rFPNJ598YlxxxRWGxWIxYmJijN/+9rcNetmxY4cxZMgQIygoyBgxYoSRmprqdi/NYfo84FlMnwfgDe58fvsZhmH4Oox1VMXFxQoLC1NRURHjhQAP+CynSL965kWlWu6T7tgrRY9pVQ0ANMedz2/uNQYAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyrm68bANC15BSWq6C0qtFtWfklXu4GAJpHEALgMTmF5Upcu1fl1TVN1owL5EQ0gI6DIATAYwpKq1ReXaN108ZoUGRoozWRpb2ll7zcGAA0gSAEwOMGRYZqZExY4xtPWrzbDAA0g3PUAADAtAhCAADAtAhCAADAtAhCAADAtAhCAADAtAhCAADAtJg+D8DjAktypJPHG994+ph3mwGAZhCEAHhUtE5r8M650rnyposCQ6SQCO81BQBNIAgB8Kiefmflf65cmrpF6j2k8aKQCCk81ruNAUAjCEIA2kfvIVL0GF93AQDNYrA0AAAwLYIQAAAwLYIQAAAwLYIQAAAwLYIQAAAwLYIQAAAwrTYFod/+9rfy8/PTokWLHM9VVFQoOTlZERERCg0N1Q033KC8vDyn1504cUKTJ09WSEiIIiMjde+99+rcuXNONXv27NFll10mi8WiQYMGaevWrQ32v2HDBl144YUKDg5WfHy8Dh486LTdlV4AAIB5tToIffDBB/rd736nSy+91On5xYsX629/+5t27typvXv36uTJk5o6dapje01NjSZPnqyqqirt379fL7zwgrZu3aoVK1Y4ao4fP67Jkydr0qRJyszM1KJFi3T77bfrzTffdNRs375dKSkpWrlypT766CONHj1aSUlJys/Pd7kXAABgckYrnD171hg8eLCxe/duY+LEicbChQsNwzCMwsJCIzAw0Ni5c6ej9siRI4YkIz093TAMw3jjjTcMf39/Izc311GzceNGw2azGZWVlYZhGMaSJUuMESNGOO1z2rRpRlJSkuPruLg4Izk52fF1TU2NER0dbaxZs8blXlpSVFRkSDKKiopcqgfM7tB/Co2fLH3aMFbaDCPnY5+9BwBzc+fzu1VnhJKTkzV58mQlJiY6PZ+RkaHq6mqn54cNG6b+/fsrPT1dkpSenq5Ro0apb9++jpqkpCQVFxfr8OHDjpr6752UlOR4j6qqKmVkZDjV+Pv7KzEx0VHjSi/1VVZWqri42OkBAAC6LrdvsbFt2zZ99NFH+uCDDxpsy83NVVBQkMLDw52e79u3r3Jzcx0154eguu1125qrKS4uVnl5uQoKClRTU9NozRdffOFyL/WtWbNGq1evbuboAQBAV+LWGaHs7GwtXLhQf/rTnxQcHNxePfnMsmXLVFRU5HhkZ2f7uiUAANCO3ApCGRkZys/P12WXXaZu3bqpW7du2rt3r5566il169ZNffv2VVVVlQoLC51el5eXp6ioKElSVFRUg5lbdV+3VGOz2WS1WtW7d28FBAQ0WnP+e7TUS30Wi0U2m83pAQAAui63gtDVV1+tQ4cOKTMz0/EYP368ZsyY4fj3wMBApaWlOV5z9OhRnThxQgkJCZKkhIQEHTp0yGl21+7du2Wz2TR8+HBHzfnvUVdT9x5BQUEaN26cU43dbldaWpqjZty4cS32AgAAzM2tMUI9evTQyJEjnZ7r3r27IiIiHM/PnTtXKSkp6tWrl2w2m375y18qISFBl19+uSTpmmuu0fDhwzVz5kw9+uijys3N1fLly5WcnCyLxSJJmj9/vp555hktWbJEc+bM0dtvv60dO3YoNTXVsd+UlBTNmjVL48ePV1xcnNatW6fS0lLNnj1bkhQWFtZiLwAAwNzcHizdkieffFL+/v664YYbVFlZqaSkJD377LOO7QEBAXr99dd15513KiEhQd27d9esWbP0wAMPOGoGDhyo1NRULV68WOvXr9cFF1yg3//+90pKSnLUTJs2TadOndKKFSuUm5urMWPGaNeuXU4DqFvqBUA9hdlS2Znma0IipPBY7/QDAO3MzzAMw9dNdFTFxcUKCwtTUVER44XQ9RVmSxvipOqy5usCQ6Tkg42Goc9yivSrZ15UquU+6Y69UvQYt9vwxHsAMDd3Pr89fkYIQCdVdqY2BE3dIvUe0njN6WPSK/NqazkrBKALIAgBcNZ7SOc5C8OlPABtRBAC0Dl54FIeABCEAHROXMoD4AEEIQCdW2e6lAegw2nVTVcBAAC6AoIQAAAwLYIQAAAwLcYIAXCSdapEFUZRo9uCT5dokJf7AYD2RBACIEnKL6lUpKSF2zJ1uIkgNMLvuFIt/60FgM6OIARAklRcXq1ISfdcM1R9hsQ1WnPqWJC097+1ANDZEYQAOIntZdWgmLBGt2Wdtnq5GwBoXwyWBgAApkUQAgAApkUQAgAApkUQAgAApkUQAgAApkUQAgAApkUQAgAApsU6QgC6pJzCcpWfqr0lSGO3DenZPUgx4ayLBJgdQQhAl5NTWK7EtXt10bkspVoav22INTBAb909kTAEmBxBCECXU1BapfLqGt2TNFTaK62/eYwqeo9ybM/KL9Gi7ZkqKK0iCAEmRxAC0GXF9qoNOYP6hErRjd82BIC5MVgaAACYFkEIAACYFkEIAACYFkEIAACYFkEIAACYFkEIAACYFkEIAACYFusIAXCbpTBLOhna4Png0yUa5Jfjg44AoHUIQgBcVhPcS2WGRbHvLJTeabh9kKT1QZK9m1X+IRFe7w8A3EUQAuCy6tAYJVY+pj9Ov7h2teZ6sk6VaOG2TD0x/YcaGh7rgw4BwD0EIQBuOanetfftauSWFRVGkQ4bRaoOjfFBZwDgPoIQYCI5heUqKK1qdNupb8s1yMv9AICvEYQAk8gpLFfi2r0qr65pdPsIv+OaZJFs1kAvdwYAvkMQAkyioLRK5dU1WjdtjAZFNjbjK0x6VYoMtfigOwDwDYIQYCLROq2R/sc1yK9hEJLfSe83BAA+RhACuorCbKnsTJObQ7NP6C3LvQp5tbLp9wgMkTrQtPesUyWqMIoaPN+ze5AYjg3AEwhCQFdQmC1tiJOqy5osuVBSmSz6+toXdWH//o0XhURIPp723rN7kIK71S56v3Bbpg43EoSsgQHaO7OnIr3dHIAuhyAEdAVlZ2pD0NQtUu8hjZZknSrRbS//S5tjJzY69b2jiAm3auPMcdJL0vqbx9RO1T9PVn6JFm3PVHF5NUEIQJsRhICupPcQKXpMo5sqjCKdVMOzKx1R3YDtQX4npXrjmYL9SzTC77gshY2McwIANxGEAHQ8IRG145Vemddg0yBJqRbV3uKjg41pAtD5EIQAdDzhsVLywUYHf9fdxmP9zWM0aMAAn49pAtC5EYQAdEzhsY2GnLrbeFT0HiWFd9yxTgA6B4IQALdl5Ze49TwAdFQEIQAu69k9SNbAAC3antlkjTUwQD27B3mvKQBoA4IQAJfFhFv11t0Tm7xxq/TdYofhVi92BQCtRxAC4JaYcCtBB0CX4e/rBgAAAHyFIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLIAQAAEyLlaWBLiTrVIkqjKLGt3FDVABogCAEdAH5JZWKlLRwW6YONxGEJG6ICgD1EYSALqC4vFqRku65Zqj6DIlrso4bogKAM4IQ0IXE9rJqUEyYr9sAgE6DwdIAAMC0CEIAAMC0CEIAAMC03ApCa9as0fe+9z316NFDkZGRmjJlio4ePepUU1FRoeTkZEVERCg0NFQ33HCD8vLynGpOnDihyZMnKyQkRJGRkbr33nt17tw5p5o9e/bosssuk8Vi0aBBg7R169YG/WzYsEEXXnihgoODFR8fr4MHD7rdCwAAMC+3gtDevXuVnJys999/X7t371Z1dbWuueYalZaWOmoWL16sv/3tb9q5c6f27t2rkydPaurUqY7tNTU1mjx5sqqqqrR//3698MIL2rp1q1asWOGoOX78uCZPnqxJkyYpMzNTixYt0u23364333zTUbN9+3alpKRo5cqV+uijjzR69GglJSUpPz/f5V4AmMTpY9LJTMcj+PQhjfA7ruDTh6TCbF93B8CXjDbIz883JBl79+41DMMwCgsLjcDAQGPnzp2OmiNHjhiSjPT0dMMwDOONN94w/P39jdzcXEfNxo0bDZvNZlRWVhqGYRhLliwxRowY4bSvadOmGUlJSY6v4+LijOTkZMfXNTU1RnR0tLFmzRqXe2lJUVGRIckoKipyqR7wlS8z/2kYK221/+ziDv2n0Bjwq9eNQ/8pbLHmiy8OG8ZDUYax0tb046Eow/hyt2HkfNz0o+CENw4NgIe48/ndpunzRUW1C7f16tVLkpSRkaHq6molJiY6aoYNG6b+/fsrPT1dl19+udLT0zVq1Cj17dvXUZOUlKQ777xThw8f1tixY5Wenu70HnU1ixYtkiRVVVUpIyNDy5Ytc2z39/dXYmKi0tPTXe4F6DQKs6WyM01uthRmebGZzqM6NEZKPtjge5d1qkQLt2Vqw8/668K0X0j/e0PzbxQYUvs+4bHt2C0AX2h1ELLb7Vq0aJEmTJigkSNHSpJyc3MVFBSk8PBwp9q+ffsqNzfXUXN+CKrbXretuZri4mKVl5eroKBANTU1jdZ88cUXLvdSX2VlpSorKx1fFxcXt/RtANpfYba0IU6qLmuyJFZSmWFRTXAv7/XVWYTHNggwFUaRDhtFKom9otGg5OT0MemVebU1BCGgy2l1EEpOTtZnn32md99915P9+NSaNWu0evVqX7cBOCs7I1WX6V77An1e3a/JsvJu4Xqx70AvNtZFNBKUAJhHq4LQggUL9Prrr2vfvn264IILHM9HRUWpqqpKhYWFTmdi8vLyFBUV5aipP7urbibX+TX1Z3fl5eXJZrPJarUqICBAAQEBjdac/x4t9VLfsmXLlJKS4vi6uLhYsbH8gkTH8Hl1P8276XoNigxtdDu3zwAA97k1a8wwDC1YsECvvvqq3n77bQ0c6PzX57hx4xQYGKi0tDTHc0ePHtWJEyeUkJAgSUpISNChQ4ecZnft3r1bNptNw4cPd9Sc/x51NXXvERQUpHHjxjnV2O12paWlOWpc6aU+i8Uim83m9AA6kkGRoRoZE9bow2whKCu/RJ/lFDX6yMov8XV7ADoJt84IJScn66WXXtL//d//qUePHo6xNmFhYbJarQoLC9PcuXOVkpKiXr16yWaz6Ze//KUSEhIcg5OvueYaDR8+XDNnztSjjz6q3NxcLV++XMnJybJYLJKk+fPn65lnntGSJUs0Z84cvf3229qxY4dSU1MdvaSkpGjWrFkaP3684uLitG7dOpWWlmr27NmOnlrqBUDn07N7kKyBAVq0PbPZOmtggHp2D/JOUwA6LbeC0MaNGyVJP/jBD5yef/755/Xzn/9ckvTkk0/K399fN9xwgyorK5WUlKRnn33WURsQEKDXX39dd955pxISEtS9e3fNmjVLDzzwgKNm4MCBSk1N1eLFi7V+/XpdcMEF+v3vf6+kpCRHzbRp03Tq1CmtWLFCubm5GjNmjHbt2uU0gLqlXgB0PjHhVr1190QVlFY1W+fKpcLmzhy5famxhZl9ColgLBLQAfkZhmH4uomOqri4WGFhYSoqKuIyGXznZKa0eaImV/5GjyyYqZHcXb7NcgrLlbh2r8qra5qssQYG6K27Jyqm7Ki0eaJ0x14pekzjxS7M7GMKPuA97nx+t2kdIQDojFo6q5SVX6JF2zNVUFqlGD8X3vC7mX2aukXqPaThdqbgAx0WQQiAKcWEWz0/wLz3kKbPGgHokAhCQEfQ3PiS08e82wsAmAhBCPA1F8aX2LtZVVDRw4tNAYA5EIQAX2tpfImkL88G6eTzx73cGAB0fQQhoKNoZnxJdU6RJIIQAHiaWytLAwAAdCUEIQAAYFpcGgM6iPySSuXnFDW6jXtnAUD7IAgBHcSdL2Yoo/p0k9u5dxYAeB5BCOggKs7ZtW7aGA2KDG10u9v3vgIAtIggBHQggyJDuZcYAHgRg6UBAIBpEYQAAIBpcWkMAJqQlV+iYP8SDZKUdapEFUbjs/qCTzdew7guoOMjCAFAPT27B8kaGKBF2zM1wu+4Ui3Swm2ZOtxEEGqqxhoYoLfunqgYbzUOwG0EIQCoJybcqrfunqiC0ioFnw6TXpXW3zxGFb1HNVrfWE1WfokWbc9UQWmVYvy82T0AdxCEAKARMeHW2stafrXLGQzqEypFNzGjz5UaAB0SQQgAXHH6WOu2AejQCEJAWxRmS2Vnmq8JiZDCY73TDzwvJEIKDJFemdd8XWBIbW1b8PMEeB1BCGitwmxpQ5xUXdZ8XWCIlHyQD6/OKjy29r9fOwWUnMJyFZRWKbAkR4N3/lD+58qbfwE/T4BHEYSA1io7UxuCpm6Reg9pvOb0sdozCWVn+ODqzMJj2+W/X05huRLX7lV5dc13M8/KtbDqf5Rl/HeeWXA3f22cOU6RoRZ+noB2QBAC2qr3EOWEDFVBaVWDTcFG7foy+SWVivR+Z+jgCkqrVF5do3XTxmikf+3Ms19Om9xg5ll+92GKZBA20C4IQkAL6i5d1Fe3iF7GiQLdmlr7V319devL3Plihp66+1IW10OjBkWGahAzzwCfIAgBzTj/0kV9dSFnxf8dlroN0gtz4hTRPcippm59mYpz9tr1ZAhCANChEISAZpx/6WJQZKjTtvMX0bMOGNd4yPELbfgcAKDDIAgBLhgUGaqRMfUuV5x/KYMzPejimrpEXIf7qqGzIggBQFfT0npEbk71b+4ScR3HfdUIQ+hkCEIA0JW4sr5VvbWIWjrbk5Vf0uQl4rrtjvuqEYTQyRCEYF6u/NUsm0d2NcgvR8GnDzU+ZojbM3RpWfklCvavnWGYdapEFefdnT4rv8TzO2xpfat6axG5crZHqj3j872BvQg66HIIQjAnF/9qDvx/aW3bT0iE7N2sWq9npVefbbLM3s2qgooebdsXOpSe3YNkDQzQou2ZjhmGT29PVZaR6VQ3LtBfkaW9pYp/N/ledYGpbsmG8wNVk2Nzeg+Rose02GdzEwLqHw8hCF0RQQjm5OJfzQEV37ZtP+Gx+vLGt5Wy9W2tv3lM7cDqRnx5Nkgnnz/etn2hQ4kJt+qtuyd+d/uMgbLv/C4QN+al7/5Z735l54cp6b9LNizclqnD3wUhT43NaXRCAGACBCGYm4t/NbdFdWiMDhsDa1cLbmKhvOqcIkkEoa4mJtz6XUAJkxZ84Pb9ys4PU5Lzkg0VvUcxNgfwAIIQTK+xgaJ1lyCyv23hBpiAq1p5v7L/hik5L9nA6tOARxCEYGr5JZVK3NhwoGjdJYi/7n5b4wJja8dwnLQ4v5hBzgDQ6RGEYGrF5dWNDhRtMKbjpSbeoN6YDgDnaWlmpuT2mkaApxGE0DW19Au43tmchgNFWzemA8B3XJmZKTVY0wjwNoIQuh43fgHXBPeSVNT49laO6QCglmdmSg3WNPIEbgUCdxGE0PW48gtYkkIiVF1qE7O1gHbkhZmZdbgVCFqDIISuy5VfwKVNnA0C0Om0tDgkyw2gMQQhAOjkzr9Vh8urT383Ti74dIlG+B2vXaOosVvANKeDjpFjcUi4gyCELq+5MQPtcq+nJjS3L2/2ga6j/srTkgurT4dE1A5QfmWeJGmQpFSLpFdb0UDdQGcP3ZMP8AWCELo0V8cM9Owe1G49NPZh5Ys+0PXUX3lacmH16fDY2vDy3YzIrFMlWrgts9lbwDTq/IHOLgSh5hYurX8z2qYw0BntgSCELs2VG0q29y/Xxj6sfNEHuianlacl11afPm9GZIVRpMNGUbO3gGmrpv4gaezsVWOidVo9/c4quJu/Ns4cp8hQS8OikAhxZgqtQRCCKfh6zECDDyvAy5q6/OqNy7JN/UFS/+xVYwJLcjR451z5n/vudjfNLG4a+P/SPNw5zIAgBACdTXO3d6m3zZVLs966LNvgDxJXzl6dPC6dK1f2pPWav6uk8Ut4312mC6j4tp06R1dGEELn4+aq0UCXUW+gc5POu/WLK5dmPXVZtqnZa1n2tp91qgwf1O6X8FzFoo1dC0EInYuLq0bbu1n15dkgZZUxGwtdSL2Bzk2qN629vS/NujJ7ratMBmDRxq6HIISOp7kzPqePOVaNzg8eoDtfzFDFOXuDsoKKHjr5fO2K0V3lFzAgqePd+uX0McX0lvbO7Kni8mrH05bCUOmd/47/6SpnSVi0seshCKFjceWMT2CI1D9B+aU2ZVSfbnZGmMRpaqBd1LtMF/ndw0lgiAYNGCCFd73FDX09AQOeQxBCx+LKfcLqTvt/d3sMfiEBPuDKZbp2WHm6sVludeORsr8t9+i+YA4EIXRMXrxRI4BW8uJlOps1sMnZb3XjkR7/x1FZAwe16VJ4SwOhc74+1uwtSQJLavfd0rIEnKnuOAhCAADfcmE5gMhQS5Oz385fj8g6YFyrA0ZLA6GjdVpvWe5VkqWyyVuSDO5m1UWBj7u0kjwDqjsGghAAwDfcXA6gydlv569H1IZg0dJA6ODThxTyaqW+vXaDevUf2fANTh+T/yvztG3mYOV3H9bkfhhQ3bEQhOAzrtx7iNPHQBfWyuUA2luT4w6/C1y9+o9s9tJ9ZKhFkW1c64i1iryHIATv+m5qfH5Jpe5qZOr7IL8crQ9yXnuE08dAF9bRlgPoAFiryLsIQvCe86bGR0r6S4CkgIZl9m5WPTH9hzpSFsbpYwCeUZit4NP/dmmgs6+xVpF3EYTgPedNjc8yorVwW2aj9w3yD4nQ0PBYVefUTo/35c0iAXQiTQ26LjstbZ+pQdVlSrWo2YHO0Xqk3dpzF0uDeAdBCN7Xe4gqjIEt3jeoI90sEkAH5sqg68AQfX3ti0r+vxO655qhiu3lfCbFUpil2HcWqqff2XZuFh0NQQgdljdvFgmgE3NxccdA9dZXqXs1+80qSc6/V0b4lSjVIgV38+80f1yxVpFnEIRQq6U7uruiHWZ2tPfNIgF0ES4Muo6RWlyLaOPMcYrs4L9zXDlbLjGg2lUEITNoKeR8d/28pTu6tygwpPavMmaAAOigWlqLKDLU4rVeWjv+0ZWz5Qyodh1BqLPzVMgJDJFu/YsU0rt1fZw+Vnt9vuwMQQgAmuGJ8Y/eOltuhvWMCEKdmSt3apdcCzmeuqzlwlL5ANBheeF3WEcZ/9hSyDlTWqX5L2a0uJ7RppnjFNFEaOsMQYkg1Jm5cqd2qVUhp6X/QaR6P+AuLpVv72bVl2eDlFXG1HcAHYibt/toVkuBKSRCMeGxXgkITV1mcyXkSLVB54U5cY0Gnbr3mPWHg82+vqOPUyII+ZIrA5RdCTEevlO7K6uaSvV+wOvN2sgvqdSdjawcXVDRQyefP+54fWeZnQGgi/PE7T7cCVPtPJ6yZ/cgXRRYoC07mlg0SdLwbv769ZRLFGYNbLLGZg1UZGSFFN6n0e3NndnqLOOUTBGENmzYoMcee0y5ubkaPXq0nn76acXFxfm2KXcua3l5AHJLq5pKTfyAnzdrIz+nSBnVp5t9j85wyhSAibT1dh+uhKm68ZQn0luc7t9sLy38IR1TdlpvWe6Rf0B58z3van6zpGY/h7rCzN4uH4S2b9+ulJQUbdq0SfHx8Vq3bp2SkpJ09OhRRUZG+q4xVy5r+XgAsiurmrY064GVUQGYSkthyhNnjVz8Q9q/rZNgJNeCm5dviutpXT4IPfHEE5o3b55mz54tSdq0aZNSU1P1hz/8QUuXLvVxd3LtslZT15vbMHCvuTFArty6glWfAaAVPHHW6PSxdhsf2uh7uLBqd3NXLjr6wo9dOghVVVUpIyNDy5Ytczzn7++vxMREpaenN6ivrKxUZWWl4+uiotp7XRUXF3u+ubMlUqVR+8+m3v9ckFQTLL18e9Pv081aW+dGjycLy/X/PfOuKqrtTdYEB/qrW02Fiov9Gt3ew196dd5YFZY1PaA6PCRIPfyrVVxc7XJvANDl+YdJoc2cKXf1d3/4SCn0gub31dbPL/8waWaaVP5t49vPZEl/u0vK+3dt7fkt1lQoyF6hu/64v9ldBAf667UFVyjag2Go7nPbMIyWi40uLCcnx5Bk7N+/3+n5e++914iLi2tQv3LlSkMSDx48ePDgwaMLPLKzs1vMCl36jJC7li1bppSUFMfXdrtd3377rSIiIuTn1/iZkY6ouLhYsbGxys7Ols1m83U77Ybj7FrMcJxmOEaJ4+xqOuNxGoahs2fPKjo6usXaLh2EevfurYCAAOXl5Tk9n5eXp6ioqAb1FotFFovz8urh4eHt2WK7stlsneaHti04zq7FDMdphmOUOM6uprMdZ1hYmEt1/u3ch08FBQVp3LhxSktLczxnt9uVlpamhIQEH3YGAAA6gi59RkiSUlJSNGvWLI0fP15xcXFat26dSktLHbPIAACAeXX5IDRt2jSdOnVKK1asUG5ursaMGaNdu3apb9++vm6t3VgsFq1cubLBZb6uhuPsWsxwnGY4Ronj7Gq6+nH6GYYrc8sAAAC6ni49RggAAKA5BCEAAGBaBCEAAGBaBCEAAGBaBKFOasOGDbrwwgsVHBys+Ph4HTx4sMnaH/zgB/Lz82vwmDx5shc7bh13jlOS1q1bp6FDh8pqtSo2NlaLFy9WRUWFl7ptPXeOs7q6Wg888IAuvvhiBQcHa/To0dq1a5cXu3Xfvn37dN111yk6Olp+fn7661//2uJr9uzZo8suu0wWi0WDBg3S1q1b273PtnL3OL/55hvdcsstGjJkiPz9/bVo0SKv9NlW7h7nK6+8oh/96Efq06ePbDabEhIS9Oabb3qn2TZw9zjfffddTZgwQREREbJarRo2bJiefPJJ7zTbBq35/7POe++9p27dumnMmDHt1l97Iwh1Qtu3b1dKSopWrlypjz76SKNHj1ZSUpLy8/MbrX/llVf0zTffOB6fffaZAgICdOONN3q5c/e4e5wvvfSSli5dqpUrV+rIkSN67rnntH37dv3617/2cufucfc4ly9frt/97nd6+umn9fnnn2v+/Pm6/vrr9fHHH3u5c9eVlpZq9OjR2rBhg0v1x48f1+TJkzVp0iRlZmZq0aJFuv322zv8h6e7x1lZWak+ffpo+fLlGj16dDt35znuHue+ffv0ox/9SG+88YYyMjI0adIkXXfddR36Z1Zy/zi7d++uBQsWaN++fTpy5IiWL1+u5cuXa/Pmze3cadu4e5x1CgsLddttt+nqq69up868xDO3N4U3xcXFGcnJyY6va2pqjOjoaGPNmjUuvf7JJ580evToYZSUlLRXix7h7nEmJycbP/zhD52eS0lJMSZMmNCufbaVu8fZr18/45lnnnF6burUqcaMGTPatU9PkWS8+uqrzdYsWbLEGDFihNNz06ZNM5KSktqxM89y5TjPN3HiRGPhwoXt1k97cfc46wwfPtxYvXq15xtqJ609zuuvv9649dZbPd9QO3HnOKdNm2YsX77cWLlypTF69Oh27as9cUaok6mqqlJGRoYSExMdz/n7+ysxMVHp6ekuvcdzzz2nm2++Wd27d2+vNtusNcf5/e9/XxkZGY7LSl999ZXeeOMN/eQnP/FKz63RmuOsrKxUcHCw03NWq1Xvvvtuu/bqTenp6U7fE0lKSkpy+WccHZvdbtfZs2fVq1cvX7fSrj7++GPt379fEydO9HUrHvf888/rq6++0sqVK33dSpt1+ZWlu5rTp0+rpqamwcrYffv21RdffNHi6w8ePKjPPvtMzz33XHu16BGtOc5bbrlFp0+f1hVXXCHDMHTu3DnNnz+/Q18aa81xJiUl6YknntBVV12liy++WGlpaXrllVdUU1PjjZa9Ijc3t9HvSXFxscrLy2W1Wn3UGTzh8ccfV0lJiW666SZft9IuLrjgAp06dUrnzp3TqlWrdPvtt/u6JY/68ssvtXTpUv3zn/9Ut26dP0ZwRshknnvuOY0aNUpxcXG+bsXj9uzZo4cffljPPvusPvroI73yyitKTU3Vgw8+6OvWPGr9+vUaPHiwhg0bpqCgIC1YsECzZ8+Wvz//O6Pje+mll7R69Wrt2LFDkZGRvm6nXfzzn//Uhx9+qE2bNmndunV6+eWXfd2Sx9TU1OiWW27R6tWrNWTIEF+34xGdP8qZTO/evRUQEKC8vDyn5/Py8hQVFdXsa0tLS7Vt2zY98MAD7dmiR7TmOO+//37NnDnT8dfXqFGjVFpaqjvuuEP33XdfhwwKrTnOPn366K9//asqKip05swZRUdHa+nSpbrooou80bJXREVFNfo9sdlsnA3qxLZt26bbb79dO3fubHDpsysZOHCgpNrfQXl5eVq1apWmT5/u46484+zZs/rwww/18ccfa8GCBZJqL3UahqFu3brpH//4h374wx/6uEv3dLxPBjQrKChI48aNU1pamuM5u92utLQ0JSQkNPvanTt3qrKyUrfeemt7t9lmrTnOsrKyBmEnICBAkmR00FvqteW/Z3BwsGJiYnTu3Dn95S9/0c9+9rP2btdrEhISnL4nkrR79+4WvyfouF5++WXNnj1bL7/8cqdYusNT7Ha7Kisrfd2Gx9hsNh06dEiZmZmOx/z58zV06FBlZmYqPj7e1y26jTNCnVBKSopmzZql8ePHKy4uTuvWrVNpaalmz54tSbrtttsUExOjNWvWOL3uueee05QpUxQREeGLtt3m7nFed911euKJJzR27FjFx8crKytL999/v6677jpHIOqI3D3OAwcOKCcnR2PGjFFOTo5WrVolu92uJUuW+PIwmlVSUqKsrCzH18ePH1dmZqZ69eql/v37a9myZcrJydEf//hHSdL8+fP1zDPPaMmSJZozZ47efvtt7dixQ6mpqb46BJe4e5ySlJmZ6XjtqVOnlJmZqaCgIA0fPtzb7bvM3eN86aWXNGvWLK1fv17x8fHKzc2VVDvIPywszCfH4Ap3j3PDhg3q37+/hg0bJql22YDHH39cd911l0/6d5U7x+nv76+RI0c6vT4yMlLBwcENnu80fDxrDa309NNPG/379zeCgoKMuLg44/3333dsmzhxojFr1iyn+i+++MKQZPzjH//wcqdt485xVldXG6tWrTIuvvhiIzg42IiNjTX+53/+xygoKPB+425y5zj37NljXHLJJYbFYjEiIiKMmTNnGjk5OT7o2nXvvPOOIanBo+64Zs2aZUycOLHBa8aMGWMEBQUZF110kfH88897vW93teY4G6sfMGCA13t3h7vHOXHixGbrOyp3j/Opp54yRowYYYSEhBg2m80YO3as8eyzzxo1NTW+OQAXtebn9nydffq8n2F00GsGAAAA7YwxQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLQIQgAAwLT+fzafz05HOorEAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here are the final populations\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 4604\n",
      "working on HD 600 out of 4604\n",
      "working on HD 1200 out of 4604\n",
      "working on HD 1800 out of 4604\n",
      "working on HD 2400 out of 4604\n",
      "working on HD 3000 out of 4604\n",
      "working on HD 3600 out of 4604\n",
      "working on HD 4200 out of 4604\n",
      "all done checking HD and complement contiguity for all 4604 HDs\n",
      "underpop contigFail, enclaveFail = 0 166 out of 756\n",
      "overpop contigFail, enclaveFail = 0 0 out of 1442\n",
      "total contigFail, enclaveFail =  0 166\n",
      "CCB unit 4019 with pop 161018.0 now has use 0.98249\n",
      "CCB unit 4020 with pop 185562.0 now has use 1.03368\n",
      "CCB unit 4021 with pop 139686.0 now has use 0.9944\n",
      "CCB unit 4022 with pop 25126.0 now has use 0.99785\n"
     ]
    }
   ],
   "source": [
    "print(\"Here are the stats prior to any equi-pop patching\")\n",
    "shedUnitUse = [0. for u in range(nUnits)]\n",
    "shedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "shedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in shedHDlist[t]:\n",
    "        shedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(latestUnitUse,bins=50,weights=unitPop,label=\"pre-squaring\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.hist(shedUnitUse, bins=50, weights=unitPop,label=\"shed\",histtype=\"step\")\n",
    "plt.legend()\n",
    "#latestAvg, latestSD = getWeightedAvgAndSD(latestUnitUse,unitPop)\n",
    "shedUnitUseAvg, shedUnitUseSD = getWeightedAvgAndSD(shedUnitUse,unitPop)\n",
    "#print(\"orig unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "print(\"shed unit avg and sd usage are\", r5(shedUnitUseAvg),  r5(shedUnitUseSD) )\n",
    "plt.show()\n",
    "# note: when I ran this early Jan, went from 0.12662 to 0.09961 to 0.09432 SD orig-amped-shed, but contig not yet done\n",
    "print(\"and here are the final populations\")\n",
    "plt.hist([shedHDpop[t] for t in popHDlist],bins=20)\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "failEnclaveSet, failContigSet = set(), set()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%600 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs,5)\n",
    "    if not noEnclave:\n",
    "        noEnclave, eList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if not unbroken or not noEnclave:\n",
    "        #print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "        pass\n",
    "    if not unbroken:\n",
    "        failContigSet.add(t)\n",
    "    if not noEnclave:\n",
    "        failEnclaveSet.add(t)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")\n",
    "failContigUnderpopped, failEnclaveUnderpopped = set(underPoppedList).intersection(failContigSet), set(underPoppedList).intersection(failEnclaveSet)\n",
    "failContigOverpopped, failEnclaveOverpopped = set(overPoppedList).intersection(failContigSet), set(overPoppedList).intersection(failEnclaveSet)\n",
    "print(\"underpop contigFail, enclaveFail =\",len(failContigUnderpopped), len(failEnclaveUnderpopped),\"out of\",len(underPoppedList))\n",
    "print(\"overpop contigFail, enclaveFail =\",len(failContigOverpopped), len(failEnclaveOverpopped),\"out of\",len(overPoppedList))\n",
    "print(\"total contigFail, enclaveFail = \",len(failContigSet), len(failEnclaveSet) )\n",
    "for u in range(nUnits):\n",
    "    if abs( allUnits[u]%1 - 0.25) < 0.01:\n",
    "        print(\"CCB unit\",u,\"with pop\",unitPop[u],\"now has use\",r5(unitUse[u]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ed668f8-bf1e-46eb-963f-cf5e2b935b11",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see MD code if we need to remove a stuck CCB's from any HDs and then redo the square-up after dropping them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "id": "e7bfa674-8fc8-42c8-86e9-76d334d3c47c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"VRAcontigGoodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "id": "3944dd16-da20-4f60-8fc8-30571e246cda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 1.00013 0.11441\n"
     ]
    }
   ],
   "source": [
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fc7131e-4fa8-4152-8e3c-45f92cc54ac8",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\") #vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology -- or read in via next block\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"VRAcontigGoodPop.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18581a7b-052f-413c-8312-0c569c0aba15",
   "metadata": {},
   "outputs": [],
   "source": [
    "#SKIP THE BELOW IF NOT A COLD RESTART\n",
    "print(\"upon restart, need to pull in unit topology and data\")  #note, this won't have geometries for plotting, but fine for patching\n",
    "topologyFile = \"enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv\"\n",
    "infile = input(topologyFile)\n",
    "topDF = pd.read_csv(infile)\n",
    "unitCPx, unitCPy, unitPop = topDF[\"centroid x\"], topDF[\"centroid y\"], topDF[\"unitPop\"]\n",
    "nUnits = len(unitPop)\n",
    "unitCP = [Point(unitCPx[u], unitCPy[u]) for u in range(nUnits) ]\n",
    "onBorder = topDF[\"onBorder\"]\n",
    "borderSet = set()\n",
    "for i, onB in enumerate(onBorder):\n",
    "    if onB == 1:\n",
    "        borderSet.add(i)\n",
    "borderList = list(borderSet)\n",
    "\n",
    "nbrListString = topDF[\"neighborList\"]\n",
    "unitNbrs = [ast.literal_eval(nbrListString[u]) for u in range(nUnits)]\n",
    "unitParentVTDno = topDF[\"unitParentVTDno\"]  #NOTE: some units are VTD fragments, so they share a parentVTDno\n",
    "uVLstring = topDF[\"unitVTDlist\"]\n",
    "unitNbrs = [ast.literal_eval(uVLstring[u]) for u in range(nUnits)]\n",
    "allUnits = topDF[\"allUnits\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1acd746d-f3e7-4d23-992a-cae9efbf040d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#needed for restart only  about 5sec per 2000 HDs\n",
    "avgDist = [0. for t in range(nHDs)]\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if t%800 == 0:\n",
    "        print(\"working avg precinct-to-HDcP distance for HD\",t)\n",
    "    if HDvPop[t] > 0.1 * aDP:\n",
    "        avgDist[t] = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        popHDlist.append(t)\n",
    "print(\"all avgDist to HD centers computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b0b39d6-e539-4fb4-a9bf-cc0c4369f431",
   "metadata": {},
   "outputs": [],
   "source": [
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "27b42f93-dc87-4afe-8eb3-f30fdff4a737",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking unitUse, pop for county clusters\n",
      "4019 0.98054 161018.0\n",
      "4020 1.03409 185562.0\n",
      "4021 0.98072 139686.0\n",
      "4022 0.98241 25126.0\n"
     ]
    }
   ],
   "source": [
    "print(\"checking unitUse, pop for county clusters\")\n",
    "for uNo in allUnits:\n",
    "    if uNo - int(uNo) > 0.23 and uNo - int(uNo) < 0.27:\n",
    "        u = allUnits.index(uNo)\n",
    "        print(u,r5(unitUse[u]), unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "id": "72941b8f-7be6-4a31-9377-618f44a34336",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unpatchedUnitUse = unitUse.copy()              #... for safekeeping\n",
    "unpatchedHDlist =  [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "unpatchedHDpop =   HDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60939a5e-e539-4016-aca1-4d07c7e198a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitUse = unpatchedUnitUse.copy()              #... for restarting\n",
    "HDunitList =  [unpatchedHDlist[t].copy() for t in range(nHDs) ]\n",
    "HDvPop =   unpatchedHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ddfabe30-e414-4c7a-aeb1-8af3773a8855",
   "metadata": {},
   "outputs": [],
   "source": [
    "#below is after an avoidedEnclave stumble in initial run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "id": "fd36caf6-71e4-44a4-9d09-7469512c5e05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used.  Using new-for-WI avoidedEnclave routines\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.07\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 690 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 120\n",
      "enter updated stopMinUse value for ending usage boost on a unit; I reco 0.98 0.98\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1395 units out of 4023 with usage below 0.98\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10 10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 38468\n",
      "current avg and SD of unit usage are 1.00015 0.09056 . Now trying to increase up to 120 units' underusage\n",
      "all done trying to increase usage of unit 1096 final usage = 0.77358 105 sec elapsed 6 87 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.09053\n",
      "Warning! Attempted to add list [1185] but it looks like an enclave\n",
      "all done trying to increase usage of unit 1187 final usage = 0.92456 163 sec elapsed 66 17 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.0884\n",
      "Warning! Attempted to add list [1200] but it looks like an enclave\n",
      "Warning! Attempted to add list [1200] but it looks like an enclave\n",
      "all done trying to increase usage of unit 1275 final usage = 0.93331 248 sec elapsed 58 40 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.08691\n",
      "all done trying to increase usage of unit 317 final usage = 0.81652 299 sec elapsed 34 26 successful, failed patches, couldn't start= 82\n",
      "current avg and SD of usage are 1.00015 0.08669\n",
      "all done trying to increase usage of unit 40 final usage = 0.98065 420 sec elapsed 86 5 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00014 0.08585\n",
      "Warning! Attempted to add list [1707] but it looks like an enclave\n",
      "Warning! Attempted to add list [1707] but it looks like an enclave\n",
      "Warning! Attempted to add list [1707] but it looks like an enclave\n",
      "Warning! Attempted to add list [1707] but it looks like an enclave\n",
      "all done trying to increase usage of unit 1185 final usage = 0.93468 519 sec elapsed 62 41 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.08464\n",
      "Warning! Attempted to add list [3023] but it looks like an enclave\n",
      "Warning! Attempted to add list [3023] but it looks like an enclave\n",
      "Warning! Attempted to add list [3023] but it looks like an enclave\n",
      "all done trying to increase usage of unit 3493 final usage = 0.98121 685 sec elapsed 108 44 successful, failed patches, couldn't start= 35\n",
      "current avg and SD of usage are 1.00015 0.08198\n",
      "Warning! Attempted to add list [1707] but it looks like an enclave\n",
      "all done trying to increase usage of unit 1165 final usage = 0.96026 798 sec elapsed 71 14 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.08054\n",
      "all done trying to increase usage of unit 1110 final usage = 0.98653 938 sec elapsed 97 31 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.07944\n",
      "begin usage increase for unit 1104 with usage 0.79419 . Sec, total UU units tried = 939 10\n",
      "all done trying to increase usage of unit 1104 final usage = 0.8644 1041 sec elapsed 36 37 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.07899\n",
      "all done trying to increase usage of unit 1103 final usage = 0.82285 1169 sec elapsed 12 61 successful, failed patches, couldn't start= 31\n",
      "current avg and SD of usage are 1.00014 0.07893\n",
      "Warning! Attempted to add list [1214] but it looks like an enclave\n",
      "all done trying to increase usage of unit 1218 final usage = 0.98023 1291 sec elapsed 108 10 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07738\n",
      "Warning! Attempted to add list [1157] but it looks like an enclave\n",
      "Warning! Attempted to add list [1157] but it looks like an enclave\n",
      "all done trying to increase usage of unit 42 final usage = 0.98063 1424 sec elapsed 74 4 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00014 0.07681\n",
      "all done trying to increase usage of unit 1602 final usage = 0.98044 1583 sec elapsed 91 38 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00013 0.07525\n",
      "all done trying to increase usage of unit 1105 final usage = 0.94323 1703 sec elapsed 82 6 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00013 0.0748\n",
      "all done trying to increase usage of unit 1097 final usage = 0.82963 1750 sec elapsed 17 11 successful, failed patches, couldn't start= 89\n",
      "current avg and SD of usage are 1.00013 0.07473\n",
      "all done trying to increase usage of unit 1305 final usage = 0.9475 1855 sec elapsed 81 8 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00013 0.07388\n",
      "all done trying to increase usage of unit 333 final usage = 0.83245 1892 sec elapsed 21 24 successful, failed patches, couldn't start= 92\n",
      "current avg and SD of usage are 1.00013 0.07383\n",
      "all done trying to increase usage of unit 1177 final usage = 0.92711 2001 sec elapsed 61 25 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00013 0.07335\n",
      "begin usage increase for unit 48 with usage 0.81052 . Sec, total UU units tried = 2002 20\n",
      "all done trying to increase usage of unit 48 final usage = 0.98166 2182 sec elapsed 71 2 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00014 0.07305\n",
      "all done trying to increase usage of unit 2074 final usage = 0.9804 2234 sec elapsed 102 37 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00014 0.07148\n",
      "all done trying to increase usage of unit 325 final usage = 0.8364 2266 sec elapsed 15 9 successful, failed patches, couldn't start= 92\n",
      "current avg and SD of usage are 1.00014 0.07132\n",
      "all done trying to increase usage of unit 1178 final usage = 0.92736 2363 sec elapsed 60 25 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00013 0.07085\n",
      "all done trying to increase usage of unit 1095 final usage = 0.83054 2417 sec elapsed 9 22 successful, failed patches, couldn't start= 79\n",
      "current avg and SD of usage are 1.00013 0.07083\n",
      "all done trying to increase usage of unit 338 final usage = 0.98311 2524 sec elapsed 74 11 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00013 0.07047\n",
      "all done trying to increase usage of unit 1192 final usage = 0.92314 2641 sec elapsed 50 53 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.06997\n"
     ]
    }
   ],
   "source": [
    "#Now using faster avoidedEnclave, avoidedIsland subroutines vs. wontEnclave\n",
    "#  updated to exclude VRA cores\n",
    "\n",
    "#FIRST PATCHING BLOCK - boosting underuse.  Suppresses long strings.  For some states (e.g. MA), do overused first. MA:over-und-over-und\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used.  Using new-for-WI avoidedEnclave routines\")\n",
    "maxSD = 0.07  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.98\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1. or u in coreUs:  #the VRA core can't be messed with\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        complementContig = avoidedEnclave(HDunitList[t], unitNbrs, UUUc)\n",
    "        #contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not complementContig: #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            complementContig  = avoidedEnclave(HDunitList[t], unitNbrs, [UUU])\n",
    "            loopUUUc = [UUU]\n",
    "        if complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in set(uuCandidates):\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop and u not in coreUs:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = avoidedEnclave(list(trySet), unitNbrs, [addU])\n",
    "                    #cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet.union(coreUset)) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap and u not in coreUs:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        cContig = avoidedIsland(list(trySet), unitNbrs, [shedU])\n",
    "                        #contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if cContig: # and contig :\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = ( set(unitNbrs[shedU]).intersection(trySet) ).difference(coreUset)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32c37801-eb8d-4f20-940b-418fe4ba61ef",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "id": "861f29d3-b727-49af-90a8-aa9a963e0741",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00013 1.00014 and their SDs are 0.11441 0.06997\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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hwzV16lS9/PLLkqTevXv7ve/NN9/U5ZdfLklasmSJRo8erYEDByosLEzZ2dmaNWuW1Tc2Nlavv/66cnNz1adPH7Vr106TJ0/mEmoAClOjrnRtsNYBhKYTDjCXX365jPnu5498X9sR8fHxeu655763z3nnnad33nnnRIcHAABCAM9CAgAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAttMkd+IFgKZy2ESr06YVwR4GgCBjBgYAANgOAQYAANgOAQaArTgdtZqTOk1zUqfxKAEghBFgANhKmBqVFfeesuLe41ECQAgjwAAAANshwAAAANshwAAAANshwAAAANshwAAAANshwAAAANvhUQIAbOWwcarb5hesdQChiQADwGYcOmyigz0IAEHGISQAAGA7BBgAthLlqNNjZ8zUY2fMVJSjLtjDARAkBBgAthKuBt0Yv1o3xq9WuBqCPRwAQUKAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtkOAAQAAtsOdeAHYymHj1AUlS6x1AKGJAAPAZhyqbIgN9iAABBmHkAAAgO0wAwPAVqIcdZrY4S+SpIe/+I1qTWSQRwQgGJiBAWAr4WrQLe1W6pZ2K3mUABDCCDAAAMB2CDAAAMB2CDAAAMB2CDAAAMB2TjjAFBQU6Nprr1VycrIcDoeWL1/u126M0eTJk9WhQwfFxMQoIyNDO3fu9OtTWVmpnJwcuVwuxcXFacSIETpw4IBfn02bNunSSy9VdHS0UlJSNGPGjBOvDgAAtEgnHGAOHjyoXr16ac6cOcdsnzFjhmbNmqV58+Zp7dq1at26tTIzM1VdXW31ycnJUUlJifLz87VixQoVFBRo1KhRVrvP59OgQYPUsWNHFRUV6dFHH9XUqVP17LPP/ogSAQBAS+Mwxpgf/WaHQy+++KKuv/56SV/PviQnJ+u+++7T/fffL0nyer1KSkrSokWLNHToUG3btk3du3fX+vXr1bdvX0lSXl6err76an322WdKTk7W3Llz9bvf/U4ej0dRUVGSpPHjx2v58uXavn37McdSU1Ojmpoa67XP51NKSoq8Xq9cLtePLREICZ3Grwz2EI6bQ406PXKfJOnzuvYyNjoSvnt6VrCHADR7Pp9PsbGxP/j7O6A/+bt27ZLH41FGRoa1LTY2VmlpaSosLJQkFRYWKi4uzgovkpSRkaGwsDCtXbvW6jNgwAArvEhSZmamSktLtX///mPue9q0aYqNjbWWlJSUQJYGoJkwCtNndUn6rC7JVuEFQGAF9Kff4/FIkpKSkvy2JyUlWW0ej0eJiYl+7REREYqPj/frc6zP+OY+vm3ChAnyer3WsmfPnpMvCAAANEst5lECTqdTTidPpgVaukhHne53/02S9JhnmOp4lAAQkgI6A+N2uyVJ5eXlftvLy8utNrfbrYqKCr/2+vp6VVZW+vU51md8cx8AQlOEGnRb+3/ptvb/UgSPEgBCVkADTOfOneV2u7V69Wprm8/n09q1a5Weni5JSk9PV1VVlYqKiqw+a9asUWNjo9LS0qw+BQUFqqurs/rk5+erS5cuatu2bSCHDAAAbOiEA8yBAwdUXFys4uJiSV+fuFtcXKyysjI5HA7dc889evjhh/Xyyy9r8+bNuuWWW5ScnGxdqdStWzddddVVGjlypNatW6f33ntPo0eP1tChQ5WcnCxJuvnmmxUVFaURI0aopKRES5cu1ZNPPqkxY8YErHAAAGBfJ3wOzIYNG3TFFVdYr4+EiuHDh2vRokV64IEHdPDgQY0aNUpVVVXq37+/8vLyFB0dbb1nyZIlGj16tAYOHKiwsDBlZ2dr1qxZVntsbKxef/115ebmqk+fPmrXrp0mT57sd68YAAAQuk7qPjDN2fFeRw7AXveBiXFUa1vPGyVJ3Ta/oMMm+gfe0XxwHxjghwXlPjAAAACnAgEGAADYTou5DwyA0FBtovTT0jnWOoDQRIABYCtGYdpZ0zHYwwAQZBxCAgAAtsMMDABbiXTUKTfxn5KkORU/51ECQIgiwACwlQg16J6kf0iSnqnIVp0IMEAo4hASAACwHQIMAACwHQIMAACwHQIMAACwHQIMAACwHQIMAACwHS6jBmArNSZSQ3Y+bq0DCE0EGAC20qhwbTp8TrCHASDIOIQEAABshxkYALYS6ajTr9u9LEla+J8hPEoACFEEGAC2EqEG/b8OCyVJf/tPFo8SAEIUh5AAAIDtEGAAAIDtEGAAAIDtEGAAAIDtEGAAAIDtEGAAAIDtcBk1AFupMZEa+u8/WusAQhMBBoCtNCpcHxw8L9jDABBkHEICAAC2wwwMAFuJUL1uSsiTJP3jy6tUz39jQEjiJx+ArUQ66vX70+dJkl6ozFC94b8xIBRxCAkAANgOAQYAANgOAQYAANgOAQYAANgOAQYAANgOAQYAANhOwANMQ0ODJk2apM6dOysmJkY/+clP9Pvf/17GGKuPMUaTJ09Whw4dFBMTo4yMDO3cudPvcyorK5WTkyOXy6W4uDiNGDFCBw4cCPRwAdhMrYnUr3dN0a93TVEtjxIAQlbAA8wjjzyiuXPn6qmnntK2bdv0yCOPaMaMGZo9e7bVZ8aMGZo1a5bmzZuntWvXqnXr1srMzFR1dbXVJycnRyUlJcrPz9eKFStUUFCgUaNGBXq4AGymQeF686sL9eZXF6pB4cEeDoAgcZhvTo0EwDXXXKOkpCTNnz/f2padna2YmBj9/e9/lzFGycnJuu+++3T//fdLkrxer5KSkrRo0SINHTpU27ZtU/fu3bV+/Xr17dtXkpSXl6err75an332mZKTk39wHD6fT7GxsfJ6vXK5XIEsEWhxOo1fGewhhITd07OCPQSg2Tve398Bn4G5+OKLtXr1au3YsUOS9NFHH+ndd9/V4MGDJUm7du2Sx+NRRkaG9Z7Y2FilpaWpsLBQklRYWKi4uDgrvEhSRkaGwsLCtHbt2mPut6amRj6fz28B0PJEqF43tn1DN7Z9QxGqD/ZwAARJwO/BPX78ePl8PnXt2lXh4eFqaGjQH/7wB+Xk5EiSPB6PJCkpKcnvfUlJSVabx+NRYmKi/0AjIhQfH2/1+bZp06bpwQcfDHQ5AJqZSEe9Hkt5QpK0sqo/jxIAQlTAZ2D++c9/asmSJXruuee0ceNGLV68WI899pgWL14c6F35mTBhgrxer7Xs2bOnSfcHAACCJ+B/uowdO1bjx4/X0KFDJUk9e/bUp59+qmnTpmn48OFyu92SpPLycnXo0MF6X3l5uXr37i1Jcrvdqqio8Pvc+vp6VVZWWu//NqfTKafTGehyAABAMxTwGZhDhw4pLMz/Y8PDw9XY2ChJ6ty5s9xut1avXm21+3w+rV27Vunp6ZKk9PR0VVVVqaioyOqzZs0aNTY2Ki0tLdBDBgAANhPwGZhrr71Wf/jDH5SamqoePXroww8/1OOPP65bb71VkuRwOHTPPffo4Ycf1tlnn63OnTtr0qRJSk5O1vXXXy9J6tatm6666iqNHDlS8+bNU11dnUaPHq2hQ4ce1xVIAACgZQt4gJk9e7YmTZqkO++8UxUVFUpOTtZtt92myZMnW30eeOABHTx4UKNGjVJVVZX69++vvLw8RUdHW32WLFmi0aNHa+DAgQoLC1N2drZmzZoV6OECAAAbCvh9YJoL7gMDHD873QcmxlGtbT1vlCR12/yCDpvoH3hH88F9YIAfdry/v7n+EICt1JpI3fnpeGsdQGgiwACwlQaF61Vv/2APA0CQ8TRqAABgO8zAALCVcDUoM/brx46s8qbzQEcgRBFgANhKlKNOT3ecLunISbwEGCAUcQgJAADYDgEGAADYDgEGAADYDgEGAADYDgEGAADYDgEGAADYDpdRA7CVOhOh+/fcY60DCE389AOwlXpF6IX9GcEeBoAg4xASAACwHWZgANhKuBo0oM1GSVLBVxfwKAEgRBFgANhKlKNOCzs/KIlHCQChjENIAADAdggwAADAdggwAADAdggwAADAdggwAADAdggwAADAdriMGoCt1JkITfr8dmsdQGjipx+ArdQrQn/78ppgDwNAkHEICQAA2A4zMABsJUwNuqh1iSRp3cEeauRRAkBIIsAAsBWno07P/+T/SeJRAkAo4xASAACwHQIMAACwHQIMAACwHQIMAACwHQIMAACwHQIMAACwHS6jBmAr9QrXH7/4tbUOIDQRYADYSp2J1LP7soM9DABB1iSHkD7//HP98pe/VEJCgmJiYtSzZ09t2LDBajfGaPLkyerQoYNiYmKUkZGhnTt3+n1GZWWlcnJy5HK5FBcXpxEjRujAgQNNMVwAAGAzAQ8w+/fv1yWXXKLIyEi99tpr2rp1q/70pz+pbdu2Vp8ZM2Zo1qxZmjdvntauXavWrVsrMzNT1dXVVp+cnByVlJQoPz9fK1asUEFBgUaNGhXo4QKwmTA16LyYHTovZofC1BDs4QAIEocxxgTyA8ePH6/33ntP77zzzjHbjTFKTk7Wfffdp/vvv1+S5PV6lZSUpEWLFmno0KHatm2bunfvrvXr16tv376SpLy8PF199dX67LPPlJyc/IPj8Pl8io2NldfrlcvlClyBQAvUafzKYA/huMU4qrWt542SjjxKIDrIIzp+u6dnBXsIQLN3vL+/Az4D8/LLL6tv3776n//5HyUmJur888/Xn//8Z6t9165d8ng8ysjIsLbFxsYqLS1NhYWFkqTCwkLFxcVZ4UWSMjIyFBYWprVr1x5zvzU1NfL5fH4LAABomQIeYD755BPNnTtXZ599tlatWqU77rhDd999txYvXixJ8ng8kqSkpCS/9yUlJVltHo9HiYmJfu0RERGKj4+3+nzbtGnTFBsbay0pKSmBLg0AADQTAQ8wjY2NuuCCC/THP/5R559/vkaNGqWRI0dq3rx5gd6VnwkTJsjr9VrLnj17mnR/AAAgeAIeYDp06KDu3bv7bevWrZvKysokSW63W5JUXl7u16e8vNxqc7vdqqio8Guvr69XZWWl1efbnE6nXC6X3wIAAFqmgAeYSy65RKWlpX7bduzYoY4dO0qSOnfuLLfbrdWrV1vtPp9Pa9euVXp6uiQpPT1dVVVVKioqsvqsWbNGjY2NSktLC/SQAQCAzQT8Rnb33nuvLr74Yv3xj3/Uz3/+c61bt07PPvusnn32WUmSw+HQPffco4cfflhnn322OnfurEmTJik5OVnXX3+9pK9nbK666irr0FNdXZ1Gjx6toUOHHtcVSAAAoGULeIC58MIL9eKLL2rChAl66KGH1LlzZz3xxBPKycmx+jzwwAM6ePCgRo0apaqqKvXv3195eXmKjv7v5ZBLlizR6NGjNXDgQIWFhSk7O1uzZs0K9HAB2Ey9wvVE+U3WOoDQFPD7wDQX3AcGOH52ug+MnXEfGOCHBe0+MAAAAE2NhzkCsBWHGnWW8+vbJHxckyLD32FASCLAALCVaEet8rvkSrLfowQABA5/ugAAANshwAAAANshwAAAANshwAAAANshwAAAANshwAAAANvhMmoAtlKvcD2z7wZrHUBoIsAAsJU6E6lpX9wa7GEACDIOIQEAANthBgaArTjUqNMj90mSPq9rz6MEgBBFgAFgK9GOWr3bbYQkHiUAhDL+dAEAALZDgAEAALZDgAEAALZDgAEAALZDgAEAALZDgAEAALbDZdQAbKVB4frrf7KsdQChiQADwFZqTaQm770j2MMAEGQcQgIAALbDDAwAmzGKD/dJkiobXJIcwR0OgKAgwACwlRhHjTb2yJHEowSAUEaAAYBTpNP4lcEewgnbPT0r2EMAjolzYAAAgO0QYAAAgO0QYAAAgO0QYAAAgO0QYAAAgO1wFRIAW2lQuF6oHGitAwhNBBgAtlJrInX/Z/cGexgAgoxDSAAAwHaYgQFgM0YxjhpJ0mHjFI8SAEJTk8/ATJ8+XQ6HQ/fcc4+1rbq6Wrm5uUpISNBpp52m7OxslZeX+72vrKxMWVlZatWqlRITEzV27FjV19c39XABNHMxjhpt63mjtvW80QoyAEJPkwaY9evX65lnntF5553nt/3ee+/VK6+8omXLluntt9/W3r17dcMNN1jtDQ0NysrKUm1trd5//30tXrxYixYt0uTJk5tyuAAAwCaaLMAcOHBAOTk5+vOf/6y2bdta271er+bPn6/HH39cV155pfr06aOFCxfq/fff1wcffCBJev3117V161b9/e9/V+/evTV48GD9/ve/15w5c1RbW9tUQwYAADbRZAEmNzdXWVlZysjI8NteVFSkuro6v+1du3ZVamqqCgsLJUmFhYXq2bOnkpKSrD6ZmZny+XwqKSk55v5qamrk8/n8FgAA0DI1yUm8zz//vDZu3Kj169cf1ebxeBQVFaW4uDi/7UlJSfJ4PFafb4aXI+1H2o5l2rRpevDBBwMwegAA0NwFfAZmz549+u1vf6slS5YoOjo60B//nSZMmCCv12ste/bsOWX7BgAAp1bAZ2CKiopUUVGhCy64wNrW0NCggoICPfXUU1q1apVqa2tVVVXlNwtTXl4ut9stSXK73Vq3bp3f5x65SulIn29zOp1yOp0BrgY4cZ3Grwz2EACgxQv4DMzAgQO1efNmFRcXW0vfvn2Vk5NjrUdGRmr16tXWe0pLS1VWVqb09HRJUnp6ujZv3qyKigqrT35+vlwul7p37x7oIQOwkUaFaWXVJVpZdYkauRcnELICPgPTpk0bnXvuuX7bWrdurYSEBGv7iBEjNGbMGMXHx8vlcumuu+5Senq6+vXrJ0kaNGiQunfvrmHDhmnGjBnyeDyaOHGicnNzmWUBQlyNiVJu2YRgDwNAkAXlTrwzZ85UWFiYsrOzVVNTo8zMTD399NNWe3h4uFasWKE77rhD6enpat26tYYPH66HHnooGMMFAADNjMMYY4I9iKbg8/kUGxsrr9crl8sV7OEghHAODFqS3dOzgj0EhJjj/f3NAWQAthLjqNbu867R7vOuUYyjOtjDARAkBBgAAGA7BBgAAGA7BBgAAGA7BBgAAGA7BBgAAGA7BBgAAGA7QbmRHQD8WI0K0xpfX2sdQGgiwACwlRoTpVt3Tw32MAAEGX++AAAA2yHAAAAA2yHAALCVGEe1tp6bra3nZvMoASCEcQ4MANtpFVYT7CEACDJmYAAAgO0QYAAAgO0QYAAAgO0QYAAAgO0QYAAAgO1wFRIAW2mUQx8cONdaBxCaCDAAbKXGODX0k+nBHgaAIOMQEgAAsB0CDAAAsB0CDABbiXFUq6j7zSrqfjOPEgBCGOfAALCdhAhfsIcAIMiYgQEAALZDgAEAALZDgAEAALZDgAEAALZDgAEAALbDVUgAbKVRDn106GxrHUBoIsAAsJUa49R1H88M9jAABBmHkAAAgO0QYAAAgO0QYADYSrSjWu92vVXvdr1V0TxKAAhZnAMDwFYcks6IqrDWAYSmgM/ATJs2TRdeeKHatGmjxMREXX/99SotLfXrU11drdzcXCUkJOi0005Tdna2ysvL/fqUlZUpKytLrVq1UmJiosaOHav6+vpADxcAANhQwAPM22+/rdzcXH3wwQfKz89XXV2dBg0apIMHD1p97r33Xr3yyitatmyZ3n77be3du1c33HCD1d7Q0KCsrCzV1tbq/fff1+LFi7Vo0SJNnjw50MMFAAA25DDGmKbcwb59+5SYmKi3335bAwYMkNfrVfv27fXcc8/pxhtvlCRt375d3bp1U2Fhofr166fXXntN11xzjfbu3aukpCRJ0rx58zRu3Djt27dPUVFRP7hfn8+n2NhYeb1euVyupiwR8NNp/MpgD6FFi3FUa1vPr//v6Lb5BR020UEeEZqb3dOzgj0EnITj/f3d5Cfxer1eSVJ8fLwkqaioSHV1dcrIyLD6dO3aVampqSosLJQkFRYWqmfPnlZ4kaTMzEz5fD6VlJQccz81NTXy+Xx+CwAAaJmaNMA0Njbqnnvu0SWXXKJzzz1XkuTxeBQVFaW4uDi/vklJSfJ4PFafb4aXI+1H2o5l2rRpio2NtZaUlJQAVwMAAJqLJg0wubm52rJli55//vmm3I0kacKECfJ6vdayZ8+eJt8ngFPPSNpRnaod1alq0uPfAJq1JruMevTo0VqxYoUKCgp0xhlnWNvdbrdqa2tVVVXlNwtTXl4ut9tt9Vm3bp3f5x25SulIn29zOp1yOp0BrgJAc1NtojVox9PBHgaAIAv4DIwxRqNHj9aLL76oNWvWqHPnzn7tffr0UWRkpFavXm1tKy0tVVlZmdLT0yVJ6enp2rx5syoqKqw++fn5crlc6t69e6CHDAAAbCbgMzC5ubl67rnn9NJLL6lNmzbWOSuxsbGKiYlRbGysRowYoTFjxig+Pl4ul0t33XWX0tPT1a9fP0nSoEGD1L17dw0bNkwzZsyQx+PRxIkTlZubyywLAAAIfICZO3euJOnyyy/3275w4UL96le/kiTNnDlTYWFhys7OVk1NjTIzM/X00/+dEg4PD9eKFSt0xx13KD09Xa1bt9bw4cP10EMPBXq4AGwm2lGtl88eI0kasvNxVXMZNRCSmvw+MMHCfWAQLNwHpmlxHxi0RNy75r+azX1gAAAAAo0AAwAAbIcAAwAAbIcAAwAAbIcAAwAAbKfJ7sQLAE3BSPqsNtFaBxCaCDAAbKXaRKv/9gXBHgaAIOMQEgAAsB1mYNCscVM4AKHAjv/XBfvme8zAALAVp6NGL511r1466145HTXBHg6AIGEGBoCthMmoV6ud1jqA0MQMDAAAsB0CDAAAsB0CDAAAsB0CDAAAsB1O4v2RuOQNAIDgIcCEEDuGLuBYvqx3BXsIAIKMAAPAVg6baPXZ+lywhwEgyDgHBgAA2A4BBgAA2A4BBoCtOB01ev7M8Xr+zPE8SgAIYZwDA8BWwmTU77Qt1jqA0MQMDAAAsB0CDAAAsB0CDAAAsB0CDAAAsB0CDAAAsB2uQgJgO4cancEeAoAgI8AAsJXDJlrdt/xvsIcBIMg4hAQAAGyHAAMAAGyHAAPAVpyOWi3oNFULOk2V01Eb7OEACBLOgQFgK2Fq1JWuDdY6gNDEDAwAALAdAgwAALAdAgwAALCdZh1g5syZo06dOik6OlppaWlat25dsIcEAACagWYbYJYuXaoxY8ZoypQp2rhxo3r16qXMzExVVFQEe2gAACDImu1VSI8//rhGjhypX//615KkefPmaeXKlVqwYIHGjx9/VP+amhrV1NRYr71eryTJ5/M1yfgaaw41yecC+H4Njmr5/u/Hr6HmkBoNVyIBwdBUv1+PfK4x5vs7mmaopqbGhIeHmxdffNFv+y233GKGDBlyzPdMmTLFSGJhYWFhYWFpAcuePXu+Nys0yxmY//znP2poaFBSUpLf9qSkJG3fvv2Y75kwYYLGjBljvW5sbFRlZaUSEhLkcDiadLxNzefzKSUlRXv27JHL5Qr2cJpMqNQpUWtLFCp1StTaEjWnOo0x+uqrr5ScnPy9/ZplgPkxnE6nnE7/J9TGxcUFZzBNxOVyBf0f1qkQKnVK1NoShUqdErW2RM2lztjY2B/s0yxP4m3Xrp3Cw8NVXl7ut728vFxutztIowIAAM1FswwwUVFR6tOnj1avXm1ta2xs1OrVq5Wenh7EkQEAgOag2R5CGjNmjIYPH66+ffvqoosu0hNPPKGDBw9aVyWFEqfTqSlTphx1iKylCZU6JWptiUKlTolaWyI71ukw5oeuUwqep556So8++qg8Ho969+6tWbNmKS0tLdjDAgAAQdasAwwAAMCxNMtzYAAAAL4PAQYAANgOAQYAANgOAQYAANgOAeYkderUSQ6H46glNzfX6lNYWKgrr7xSrVu3lsvl0oABA3T48GG/z1m5cqXS0tIUExOjtm3b6vrrr/drLysrU1ZWllq1aqXExESNHTtW9fX1fn3eeustXXDBBXI6nTrrrLO0aNGio8Y7Z84cderUSdHR0UpLS9O6detOWa1vvfXWMd/vcDi0fv166zM2bdqkSy+9VNHR0UpJSdGMGTOOGsuyZcvUtWtXRUdHq2fPnnr11Vf92o0xmjx5sjp06KCYmBhlZGRo586dp6xWSdqxY4euu+46tWvXTi6XS/3799ebb77pt59gf6+BqHPjxo366U9/qri4OCUkJGjUqFE6cOBAs6rzh2rdvXv3d/7bXLZs2Smvo7q6Wrm5uUpISNBpp52m7Ozso27s2dS13n333erTp4+cTqd69+59zP0E+2f1ZOv86KOPdNNNNyklJUUxMTHq1q2bnnzyyaP20xK+0y+//FJXXXWVkpOT5XQ6lZKSotGjRx/1QMbmUOtxO+knL4a4iooK88UXX1hLfn6+kWTefPNNY4wx77//vnG5XGbatGlmy5YtZvv27Wbp0qWmurra+owXXnjBtG3b1sydO9eUlpaakpISs3TpUqu9vr7enHvuuSYjI8N8+OGH5tVXXzXt2rUzEyZMsPp88sknplWrVmbMmDFm69atZvbs2SY8PNzk5eVZfZ5//nkTFRVlFixYYEpKSszIkSNNXFycKS8vPyW11tTU+L3/iy++ML/5zW9M586dTWNjozHGGK/Xa5KSkkxOTo7ZsmWL+cc//mFiYmLMM888Y43jvffeM+Hh4WbGjBlm69atZuLEiSYyMtJs3rzZ6jN9+nQTGxtrli9fbj766CMzZMgQ07lzZ3P48OFT9r2effbZ5uqrrzYfffSR2bFjh7nzzjtNq1atzBdffNFsvteTrfPzzz83bdu2NbfffrvZvn27Wbdunbn44otNdna2tY/mUOcP1VpfX3/Uv80HH3zQnHbaaearr7465XXcfvvtJiUlxaxevdps2LDB9OvXz1x88cXHVWcgajXGmLvuuss89dRTZtiwYaZXr15H7aM5/KyebJ3z5883d999t3nrrbfMv//9b/O3v/3NxMTEmNmzZ1v7aCnfaWVlpXn66afN+vXrze7du80bb7xhunTpYm666aZmV+vxIsAE2G9/+1vzk5/8xPqFnJaWZiZOnPid/evq6szpp59u/vKXv3xnn1dffdWEhYUZj8djbZs7d65xuVympqbGGGPMAw88YHr06OH3vl/84hcmMzPTen3RRReZ3Nxc63VDQ4NJTk4206ZNO7Ei/8+J1vpttbW1pn379uahhx6ytj399NOmbdu2Vl3GGDNu3DjTpUsX6/XPf/5zk5WV5fdZaWlp5rbbbjPGGNPY2Gjcbrd59NFHrfaqqirjdDrNP/7xjxMr8v+caK379u0zkkxBQYG1zefzGUkmPz/fGNM8v9cTrfOZZ54xiYmJpqGhwdq2adMmI8ns3Lmz2dZ5rFq/rXfv3ubWW2+1Xp+qOqqqqkxkZKRZtmyZ1Wfbtm1GkiksLDwltX7TlClTjhlgmuPP6snUecSdd95prrjiCut1S/xOj3jyySfNGWecYb1urrV+Fw4hBVBtba3+/ve/69Zbb5XD4VBFRYXWrl2rxMREXXzxxUpKStJll12md99913rPxo0b9fnnnyssLEznn3++OnTooMGDB2vLli1Wn8LCQvXs2dPv6dyZmZny+XwqKSmx+mRkZPiNJzMzU4WFhdbYioqK/PqEhYUpIyPD6tPUtX7byy+/rC+//NLv7sqFhYUaMGCAoqKi/OooLS3V/v37j6vWXbt2yePx+PWJjY1VWlraKas1ISFBXbp00V//+lcdPHhQ9fX1euaZZ5SYmKg+ffpYdTSn7/XH1FlTU6OoqCiFhf33v5KYmBhJsvo1tzqPVeu3FRUVqbi4WCNGjLC2nao6ioqKVFdX59ena9euSk1NPWW1Ho/m9rMaqDq9Xq/i4+P96myJ3+nevXv1r3/9S5dddlmzrvX7EGACaPny5aqqqtKvfvUrSdInn3wiSZo6dapGjhypvLw8XXDBBRo4cKB1jPebfSZOnKgVK1aobdu2uvzyy1VZWSlJ8ng8fv9pSrJeezye7+3j8/l0+PBh/ec//1FDQ8Mx+xz5jKau9dvmz5+vzMxMnXHGGda2k6n1m+3ffF8wanU4HHrjjTf04Ycfqk2bNoqOjtbjjz+uvLw8tW3b9qRrbYrv9cfUeeWVV8rj8ejRRx9VbW2t9u/fr/Hjx0uSvvjii2ZZ57Fq/bb58+erW7duuvjii61tp6oOj8ejqKgoxcXFBa3W49HcflYDUef777+vpUuXatSoUda2lvad3nTTTWrVqpVOP/10uVwu/eUvf2nWtX4fAkwAzZ8/X4MHD1ZycrKkrx9AKUm33Xabfv3rX+v888/XzJkz1aVLFy1YsMCvz+9+9ztlZ2erT58+Wrhw4VEn1DU3P6bWb/rss8+0atWqE/6rLxh+TK3GGOXm5ioxMVHvvPOO1q1bp+uvv17XXnut9Yu9ufkxdfbo0UOLFy/Wn/70J7Vq1Uput1udO3dWUlKS36xMc/PtWr/p8OHDeu6552zxb/N4hEqtJ1vnli1bdN1112nKlCkaNGhQUw71pJ1MrTNnztTGjRv10ksv6d///rfGjBnT1MNtMs33fxib+fTTT/XGG2/oN7/5jbWtQ4cOkqTu3bv79e3WrZvKysq+s4/T6dSZZ55p9XG73UedwX3ktdvt/t4+LpdLMTExateuncLDw4/Z58hnNHWt37Rw4UIlJCRoyJAhfttPptZvtn/zfcfqc7x+bK1r1qzRihUr9Pzzz+uSSy7RBRdcoKeffloxMTFavHjxSdca6O/1ZL7Tm2++WR6PR59//rm+/PJLTZ06Vfv27dOZZ57Z7Or8rlq/6YUXXtChQ4d0yy23+G0/VXW43W7V1taqqqoqaLUej+b0s3qydW7dulUDBw7UqFGjNHHiRL+2lvadut1ude3aVUOGDNEzzzyjuXPnWn9UNbdafwgBJkAWLlyoxMREZWVlWds6deqk5ORklZaW+vXdsWOHOnbsKEnWZYrf7FNXV6fdu3dbfdLT07V582ZVVFRYffLz8+VyuaxfLunp6Vq9erXffvLz85Weni5JioqKUp8+ffz6NDY2avXq1Vafpq71CGOMFi5cqFtuuUWRkZF+benp6SooKFBdXZ1fHV26dLEOvfxQrZ07d5bb7fbr4/P5tHbt2lNW66FDhyTpqFmIsLAwa2ajOX2vJ/udSl9PEZ922mlaunSpoqOj9dOf/rTZ1fldtX7T/PnzNWTIELVv395v+6mqo0+fPoqMjPTrU1paqrKyslNW6/FoTj+rJ1NnSUmJrrjiCg0fPlx/+MMfjllnS/1Oj/xfVFNTI6n51fqDAnpKcIhqaGgwqampZty4cUe1zZw507hcLrNs2TKzc+dOM3HiRBMdHW0+/vhjq89vf/tbc/rpp5tVq1aZ7du3mxEjRpjExERTWVlpjPnv5ZuDBg0yxcXFJi8vz7Rv3/6Yl2+OHTvWbNu2zcyZM+eYl785nU6zaNEis3XrVjNq1CgTFxfnd1VFU9dqjDFvvPGGkWS2bdt21GdUVVWZpKQkM2zYMLNlyxbz/PPPm1atWh11aWZERIR57LHHzLZt28yUKVOOeWlmXFyceemll8ymTZvMddddd0KXUZ9srfv27TMJCQnmhhtuMMXFxaa0tNTcf//9JjIy0hQXFxtjms/3erLf6ezZs01RUZEpLS01Tz31lImJiTFPPvmk1d5c6vyhWo0xZufOncbhcJjXXnvtqLZTWcftt99uUlNTzZo1a8yGDRtMenq6SU9PP+46T7bWI+0ffvihue2228w555xjPvzwQ/Phhx9aVx01l5/Vk6lz8+bNpn379uaXv/yl3yXIFRUVVp+W8p2uXLnSLFiwwGzevNns2rXLrFixwnTr1s1ccsklzbLW40GACYBVq1YZSaa0tPSY7dOmTTNnnHGGadWqlUlPTzfvvPOOX3ttba257777TGJiomnTpo3JyMgwW7Zs8euze/duM3jwYBMTE2PatWtn7rvvPlNXV+fX58033zS9e/c2UVFR5swzzzQLFy48aiyzZ882qampJioqylx00UXmgw8+OKW1GmPMTTfd9L33BPjoo49M//79jdPpNKeffrqZPn36UX3++c9/mnPOOcdERUWZHj16mJUrV/q1NzY2mkmTJpmkpCTjdDrNwIEDv3PMTVXr+vXrzaBBg0x8fLxp06aN6devn3n11Vf9+jSH7/Vk6xw2bJiJj483UVFR5rzzzjN//etfj/qM5lDn8dQ6YcIEk5KS4ndZeDDqOHz4sLnzzjtN27ZtTatWrczPfvYz6/5Bp6rWyy67zEg6atm1a5fVpzn8rJ5MnVOmTDlmjR07dvTr1xK+0zVr1pj09HQTGxtroqOjzdlnn23GjRtn9u/f3yxrPR4OY4wJ7JwOAABA0+IcGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDsEGAAAYDv/HwGzX0Rd2DDPAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 4604\n",
      "uh-oh, HD 21 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 22 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 121 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 135 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 144 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 147 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 169 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 171 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 173 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 179 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 234 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 287 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 381 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 388 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 444 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 456 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 467 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 471 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 496 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 497 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 498 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 499 has contiguity, complement-contiguity of True False\n",
      "working on HD 500 out of 4604\n",
      "uh-oh, HD 500 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 501 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 506 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 510 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 546 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 548 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 553 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 618 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 621 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 691 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 703 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 762 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 774 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 890 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 892 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 957 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 980 has contiguity, complement-contiguity of True False\n",
      "working on HD 1000 out of 4604\n",
      "uh-oh, HD 1008 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1058 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1080 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1104 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1106 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1121 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1179 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1180 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1198 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1456 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1461 has contiguity, complement-contiguity of True False\n",
      "working on HD 1500 out of 4604\n",
      "uh-oh, HD 1506 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1525 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1527 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1528 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1542 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1544 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1564 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1604 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1606 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1612 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1644 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1650 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1776 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1855 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1856 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1858 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1859 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1860 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1864 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1866 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1869 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1870 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1871 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1874 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1878 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1879 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1890 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1900 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1901 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1902 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1903 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1908 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1913 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1916 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 1957 has contiguity, complement-contiguity of True False\n",
      "working on HD 2000 out of 4604\n",
      "uh-oh, HD 2030 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2047 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2048 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2053 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2055 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2066 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2093 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2103 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2125 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2126 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2129 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2135 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2138 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2156 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2168 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2171 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2235 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2250 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2410 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2495 has contiguity, complement-contiguity of True False\n",
      "working on HD 2500 out of 4604\n",
      "uh-oh, HD 2504 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2539 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2560 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2563 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2587 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2591 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2592 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2598 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2607 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2637 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2638 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2649 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2659 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2680 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2701 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2736 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2740 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2800 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2809 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2858 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2862 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2873 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2874 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2878 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2883 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 2906 has contiguity, complement-contiguity of True False\n",
      "working on HD 3000 out of 4604\n",
      "uh-oh, HD 3025 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3028 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3052 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3073 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3212 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3437 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3473 has contiguity, complement-contiguity of True False\n",
      "working on HD 3500 out of 4604\n",
      "uh-oh, HD 3508 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3510 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3530 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3567 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3583 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3682 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3700 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3747 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3817 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3847 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3853 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3855 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3865 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 3952 has contiguity, complement-contiguity of True False\n",
      "working on HD 4000 out of 4604\n",
      "uh-oh, HD 4038 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4039 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4091 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4188 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4308 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4382 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4419 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4442 has contiguity, complement-contiguity of True False\n",
      "working on HD 4500 out of 4604\n",
      "uh-oh, HD 4525 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4528 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4532 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4589 has contiguity, complement-contiguity of True False\n",
      "uh-oh, HD 4603 has contiguity, complement-contiguity of True False\n",
      "all done checking HD and complement contiguity for all 4604 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"up-patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "id": "26fc8551-50a9-4acd-ad4d-1b97b8a7f4b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avoidedIsland or avoidedEnclave not working properly.  Save classifications and triage\n",
      "checking for discontiguities for HD 0\n",
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "checking for discontiguities for HD 4500\n",
      "out of 4604 total HDs, there were 4439 0 165 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "print(\"legitSwap check not working properly.  Save classifications and then triage\")\n",
    "\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "id": "d33ee02a-a08a-4898-80ec-b0b437ff5278",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ePops = list()\n",
    "for t in enclaveOnly:\n",
    "    enclaveLists = getEnclaveLists(HDunitList[t],unitNbrs)\n",
    "    ePop = np.sum([np.sum([unitPop[u] for u in eL]) for eL in enclaveLists ])\n",
    "    ePops.append(ePop)\n",
    "plt.hist([ePop/aDP for ePop in ePops],bins=50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "id": "5ad8f1ac-6614-4230-9199-afc9844743dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 807832 district pop vs 769364 target\n",
      "working on enclave-y HD 21 . We have evaluated 0 of 165 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 1506 . We have evaluated 50 of 165 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 2171 . We have evaluated 100 of 165 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 3865 . We have evaluated 150 of 165 enclavy HDs.Time is now 1\n",
      "Of these, 142 wouldn't be over 807832 if all enclaves filled, while 23 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #filling all enclave pops small enough to add; we will reduce pop later\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)  #we will trim down later\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(enclaveOnly):\n",
    "    if iii%50 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(enclaveOnly),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nOrigEnclaves[t] = len(enclaveLists)\n",
    "    totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "    if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "        canFill.append(t)\n",
    "        for eL in enclaveLists:\n",
    "            HDunitList[t] += eL\n",
    "            HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "    else:\n",
    "        cantFill.append(t)\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "id": "c30cfdaf-6e32-4105-a1ca-15e2f9cea63d",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "id": "e0265054-21ca-4143-b807-c5fae1a9ee81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now trim down the overpopped we just created.  Don't use the avoidedIsland\n",
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 34 overPopped HDs to within 882\n",
      "working on squaring down HD 135 time is now 0\n",
      "We have addressed overpop in a total of 34 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now trim down the overpopped we just created.  Don't use the avoidedIsland\")\n",
    "#SQUARING DOWN  #the barred set is dynamic; we stop shedding upon underuse. \n",
    "#   now with avoidedIsland timesaver,  \n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "#HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "#HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "#unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))  \n",
    "barredSet = set(list(barredJettisonSet))\n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    for u in origBarredJettisonSet:\n",
    "        if unitUse[u] < 1.00:\n",
    "            barredSet = barredSet.union({u})  #adding back in when become underused (new for VA)\n",
    "    if ii%60 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "        #barredSet = barredJettisonSet  #see above for VA-on modification\n",
    "        #barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)  #weaker specification - must be close to be barred\n",
    "\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                #contig = avoidedIsland(tryList, unitNbrs, [unitNoToShed] )  #this is faster, but may be faulty\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    #if contig:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                      u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )\n",
    "\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList]) #ampedHDpop is wrong here\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "id": "dd100e70-fc3f-46a0-9f47-77d5d8c22cad",
   "metadata": {},
   "outputs": [],
   "source": [
    "savedHDlist = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "id": "0f593194-4a74-46e1-85aa-7be50e752f8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will now force all in 23 listToFix to be contiguous and nil-enclave\n",
      "Let's first recalc unitUse\n",
      "Strategy:  1 - reduce HD to its primary contiguous piece.\n",
      "  If this is enclavy, fill enclaves if can do under aDP.  If too much enclave pop, remove some border units from this contig piece\n",
      "  If discontig piece not enclavy, simply grow contiguously until fill\n",
      "fixing HD 21 0 of 23 elapsed sec = 0\n",
      "for HD 121 we are starting from the home unit 92 . Working on fixable HD 2\n",
      "fixing HD 1871 10 of 23 elapsed sec = 414\n",
      "fixing HD 3530 20 of 23 elapsed sec = 915\n"
     ]
    }
   ],
   "source": [
    "listToFix = cantFill.copy()\n",
    "print(\"we will now force all in\",len(listToFix),\"listToFix to be contiguous and nil-enclave\")\n",
    "print(\"Let's first recalc unitUse\")\n",
    "unitUse = [0.]*nUnits\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "\n",
    "print(\"Strategy:  1 - reduce HD to its primary contiguous piece.\")\n",
    "print(\"  If this is enclavy, fill enclaves if can do under aDP.  If too much enclave pop, remove some border units from this contig piece\")\n",
    "print(\"  If discontig piece not enclavy, simply grow contiguously until fill\")\n",
    "CCBset = set()\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop)\n",
    "for j in range(nCCBs):\n",
    "    CCBset.add( allUnits.index(j+0.25) )\n",
    "    \n",
    "for ijk,t in enumerate(listToFix):\n",
    "    if ijk%10 == 0:\n",
    "        SEC = r3(time.time()-startTime)\n",
    "        print(\"fixing HD\",t,ijk,\"of\",len(listToFix),\"elapsed sec =\",int(SEC) )\n",
    "    uCenterDist = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t]]\n",
    "    starterU = HDunitList[t][uCenterDist.index(np.min(uCenterDist))]\n",
    "    contigUs = getContigFromStarter(starterU,HDunitList[t],unitNbrs)\n",
    "    contigPop = np.sum([unitPop[u] for u in contigUs])\n",
    "    enclaveLists = getEnclaveLists(contigUs,unitNbrs)\n",
    "    ePop = np.sum([np.sum([unitPop[uu] for uu in eL]) for eL in enclaveLists])\n",
    "    shedBorderSet = set()\n",
    "    if ePop < 0.1 * aDP or contigPop + ePop < 1.2 * aDP:\n",
    "        contigList = contigUs.copy()\n",
    "        for eL in enclaveLists:\n",
    "            contigList += eL\n",
    "    else:  #severe enclave.  Jettison all but closest contiguous set of in HD border units, unless ...\n",
    "        #   we have a CCBu, then that is the starter for the contig boundary list we're saving (to not jettison too many CCBus)\n",
    "        contigBorderUs = list(set(contigUs).intersection(borderSet))\n",
    "        if len(contigBorderUs) > 0:\n",
    "            hasCCBu, CCBu = False, -999\n",
    "            CCBsInHD = set(contigBorderUs).intersection(CCBset)\n",
    "            for u in CCBsInHD:\n",
    "                hasCCBu = True  #these will be found in random order\n",
    "                CCBu = u\n",
    "            if hasCCBu:\n",
    "                starterBorderU = CCBu\n",
    "            else:\n",
    "                borderDist = [hdCP[t].distance(unitCP[u]) for u in contigBorderUs]\n",
    "                starterBorderU = borderDist.index(np.min(borderDist))\n",
    "            keptBorderUs = getContigFromStarter(starterBorderU, contigBorderUs, unitNbrs)\n",
    "            shedBorderUset = set(contigBorderUs).difference(set(keptBorderUs))  #this is like a MUSTFREE operation\n",
    "    contigList = list( set(contigList).difference(shedBorderUset) )\n",
    "\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(contigList, unitNbrs,6)\n",
    "    if not (unbroken and noEnclave):  #likely that jettisoning border units created a discontiguity\n",
    "        contigList = [starterU]  #KISS\n",
    "        print(\"for HD\",t,\"we are starting from the home unit\",starterU,\". Working on fixable HD\",ijk)\n",
    "    \n",
    "    contigPop = np.sum([unitPop[u] for u in contigList])\n",
    "    currPoly = hdCP[t]\n",
    "    for u in contigList:\n",
    "        currPoly = currPoly.union(unitCP[u])  #draw a crude 'polygon' = points collection for below distance calc\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigList.copy(), list()\n",
    "    adjoiners = list(set(getAdjoiners(currList, unitNbrs)).difference(coreUset))  #exclude core VRA units\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "        currPoly) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "    stillGoing = True\n",
    "\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap and uu not in coreUset:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                        currPoly) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigList)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigList + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    #HDnAddedUnits[t] = len(addedList)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "id": "a2fc1015-5750-4275-909b-0841c8ffa4e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rechecking contiguity ...\n",
      "checking for discontiguities for HD 0\n",
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "checking for discontiguities for HD 4500\n",
      "out of 4604 total HDs, there were 4604 0 0 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "print(\"rechecking contiguity ...\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "id": "8603640a-707c-4b87-a76e-ce571515774a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t]/aDP for t in popHDlist],bins=50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "id": "1ee72cf0-618e-411f-aa37-518ac2c679ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "#optional intermediate save\n",
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"VRAunderPatched.csv\" #\"contigUnpatchedB.csv\"  #underPatched\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "id": "31ad110c-5b9f-4a7a-aad4-2a27f475ab34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.04  is default maxSD.  Enter updated value\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "e.g. 0.04  0.04\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.02\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1230 units out of 4023 with usage above 1.02\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 38468\n",
      "current avg and SD of unit usage are 1.00006 0.06966 . Now trying to reduce up to 1230 units' overusage\n",
      "starting to reduce usage for unit 3138 with usage 1.25112 . Total units tried = 1\n",
      "try to drop unit 3138 from 20 th HD.  usage down to 1.2316417795019998\n",
      "try to drop unit 3138 from 40 th HD.  usage down to 1.1975629874865803\n",
      "try to drop unit 3138 from 60 th HD.  usage down to 1.1620193494205346\n",
      "try to drop unit 3138 from 80 th HD.  usage down to 1.142436944275247\n",
      "try to drop unit 3138 from 100 th HD.  usage down to 1.114560676974637\n",
      "all done trying to reduce usage of unit 3138 final usage = 1.1111 144 sec elapsed 103 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00006 0.0661\n",
      "starting to reduce usage for unit 3845 with usage 1.25812 . Total units tried = 2\n",
      "try to drop unit 3845 from 47 th HD.  usage down to 1.210023927226914\n",
      "try to drop unit 3845 from 94 th HD.  usage down to 1.1524504083160862\n",
      "try to drop unit 3845 from 141 th HD.  usage down to 1.0833829820177783\n",
      "all done trying to reduce usage of unit 3845 final usage = 1.01725 501 sec elapsed 130 5 successful, failed patches, couldn't start= 38\n",
      "current avg and SD of usage are 1.00007 0.06308\n",
      "starting to reduce usage for unit 5 with usage 1.21371 . Total units tried = 3\n",
      "try to drop unit 5 from 49 th HD.  usage down to 1.17175076235846\n",
      "try to drop unit 5 from 98 th HD.  usage down to 1.154930378382277\n",
      "try to drop unit 5 from 147 th HD.  usage down to 1.1476321436225005\n",
      "try to drop unit 5 from 196 th HD.  usage down to 1.1092601958792914\n",
      "try to drop unit 5 from 245 th HD.  usage down to 1.0318196211709243\n",
      "all done trying to reduce usage of unit 5 final usage = 1.02994 518 sec elapsed 80 0 successful, failed patches, couldn't start= 165\n",
      "current avg and SD of usage are 1.00005 0.05979\n",
      "starting to reduce usage for unit 695 with usage 1.19482 . Total units tried = 4\n",
      "try to drop unit 695 from 40 th HD.  usage down to 1.1534629327823152\n",
      "try to drop unit 695 from 80 th HD.  usage down to 1.0717824931075377\n",
      "all done trying to reduce usage of unit 695 final usage = 1.01708 540 sec elapsed 63 0 successful, failed patches, couldn't start= 36\n",
      "current avg and SD of usage are 1.00004 0.05603\n",
      "starting to reduce usage for unit 2979 with usage 1.17954 . Total units tried = 5\n",
      "try to drop unit 2979 from 57 th HD.  usage down to 1.1286723305430955\n",
      "try to drop unit 2979 from 114 th HD.  usage down to 1.0836767310927053\n",
      "try to drop unit 2979 from 171 th HD.  usage down to 1.0304041665576738\n",
      "all done trying to reduce usage of unit 2979 final usage = 1.01848 749 sec elapsed 170 0 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00004 0.05271\n",
      "starting to reduce usage for unit 273 with usage 1.16161 . Total units tried = 6\n",
      "try to drop unit 273 from 36 th HD.  usage down to 1.0871601272024476\n",
      "all done trying to reduce usage of unit 273 final usage = 1.01185 777 sec elapsed 52 0 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 1.00003 0.05013\n",
      "starting to reduce usage for unit 3825 with usage 1.24889 . Total units tried = 7\n",
      "try to drop unit 3825 from 31 th HD.  usage down to 1.2143053849826941\n",
      "try to drop unit 3825 from 62 th HD.  usage down to 1.1674381100106508\n",
      "try to drop unit 3825 from 93 th HD.  usage down to 1.1305583035860929\n",
      "try to drop unit 3825 from 124 th HD.  usage down to 1.073615175389155\n",
      "all done trying to reduce usage of unit 3825 final usage = 1.01811 1211 sec elapsed 142 1 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00003 0.04712\n",
      "starting to reduce usage for unit 408 with usage 1.12152 . Total units tried = 8\n",
      "try to drop unit 408 from 39 th HD.  usage down to 1.1094044708674184\n",
      "try to drop unit 408 from 78 th HD.  usage down to 1.0747979703368675\n",
      "all done trying to reduce usage of unit 408 final usage = 1.01824 1259 sec elapsed 59 26 successful, failed patches, couldn't start= 17\n",
      "current avg and SD of usage are 1.00002 0.04563\n",
      "starting to reduce usage for unit 382 with usage 1.12597 . Total units tried = 9\n",
      "try to drop unit 382 from 38 th HD.  usage down to 1.116871676334011\n",
      "try to drop unit 382 from 76 th HD.  usage down to 1.0607747014458204\n",
      "all done trying to reduce usage of unit 382 final usage = 1.01817 1280 sec elapsed 39 0 successful, failed patches, couldn't start= 50\n",
      "current avg and SD of usage are 1.00001 0.04436\n",
      "starting to reduce usage for unit 658 with usage 1.15297 . Total units tried = 10\n",
      "try to drop unit 658 from 47 th HD.  usage down to 1.099766641705577\n",
      "try to drop unit 658 from 94 th HD.  usage down to 1.0396832579111999\n",
      "all done trying to reduce usage of unit 658 final usage = 1.01719 1335 sec elapsed 57 0 successful, failed patches, couldn't start= 49\n",
      "current avg and SD of usage are 1.00001 0.04328\n",
      "starting to reduce usage for unit 3760 with usage 1.11955 . Total units tried = 11\n",
      "try to drop unit 3760 from 61 th HD.  usage down to 1.0280723708036184\n",
      "all done trying to reduce usage of unit 3760 final usage = 1.01841 1457 sec elapsed 62 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00002 0.04165\n",
      "starting to reduce usage for unit 2008 with usage 1.09764 . Total units tried = 12\n",
      "try to drop unit 2008 from 34 th HD.  usage down to 1.0807197437234295\n",
      "try to drop unit 2008 from 68 th HD.  usage down to 1.063223476919983\n",
      "try to drop unit 2008 from 102 th HD.  usage down to 1.0590200056442722\n",
      "try to drop unit 2008 from 136 th HD.  usage down to 1.051546301304341\n",
      "try to drop unit 2008 from 170 th HD.  usage down to 1.03889299491317\n",
      "all done trying to reduce usage of unit 2008 final usage = 1.03889 1470 sec elapsed 27 0 successful, failed patches, couldn't start= 147\n",
      "current avg and SD of usage are 1.00001 0.04082\n",
      "starting to reduce usage for unit 205 with usage 1.09611 . Total units tried = 13\n",
      "try to drop unit 205 from 35 th HD.  usage down to 1.0569897576131464\n",
      "all done trying to reduce usage of unit 205 final usage = 1.0188 1507 sec elapsed 30 14 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00001 0.03971\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  using 5/24/24 new avoidedIsland method\n",
    "#corrected 5/26 for MO OUUc-intrsxn  #updated to exclude VRA cores\n",
    "maxSD = 0.04 #0.06  #0.08  #0.04\n",
    "print(maxSD,\" is default maxSD.  Enter updated value\")\n",
    "maxSD = float(input(\"e.g. 0.04 \"))\n",
    "stopMaxUse = 1.02  #1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.05*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP \n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "#maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the districts a unit is drawn into\n",
    "#maxNtries = 10 #overrirde\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #each round, find the (5) most overused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nBigFound, bigUsers = 0,0,list()\n",
    "    while nBigFound < nBigUsers:\n",
    "        consideredBigU = idx[-idxNo-1]\n",
    "        if consideredBigU not in attemptedBigUs + coreUs:\n",
    "            bigUsers.append(consideredBigU)\n",
    "            nBigFound +=1\n",
    "        idxNo +=1\n",
    "    OUUclusters = [ [b] + unitNbrs[b] for b in bigUsers ]\n",
    "    bigOverUse = [np.sum([(unitUse[j] - 1.) for j in OUUclusters[i] ]) for i in range(nBigUsers) ]\n",
    "    bigI = bigOverUse.index(np.max(bigOverUse))\n",
    "    OUU = bigUsers[ bigI ]  #pick the unit that centers cluster with most overuse\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    OUUc = OUUclusters[bigI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1. or u in coreUs:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUU2nbrSet = set( unitNbrs[OUU])\n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.union(set(unitNbrs[u])) \n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.difference({u})\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUU2nbrSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OUUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists) #work from farthest HD in\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.5*len(ouuHDs): #arbitrarily only examine 50% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        #contig = avoidedIsland(HDunitList[t], unitNbrs, list( set(OUUc).intersection(set(HDunitList[t])) ) )\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        #if not contig:\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                #trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "                #contig = avoidedIsland(HDunitList[t], unitNbrs, [OUU])\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))\n",
    "        if contig and complementContig:  #if contig  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop and u not in coreUs:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    #contig = avoidedIsland(list(trySet), unitNbrs, [shedU])  #avoidedI is buggy\n",
    "                    if contig and cContig:  #if contig\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = ( set(unitNbrs[shedU]).intersection(trySet) ).difference(coreUset)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t]+coreUs and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative)  #NEW FOR GA 3/11/24\n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...  \n",
    "                    #canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    canAdd = avoidedEnclave(list(trySet), unitNbrs, [unitNoToAdd])\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist+coreUs and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= 2.* maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
   "id": "64166f72-a484-4568-a886-c7610f6c7f17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rechecking contiguity ...\n",
      "checking for discontiguities for HD 0\n",
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "checking for discontiguities for HD 4500\n",
      "out of 4604 total HDs, there were 4604 0 0 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "print(\"rechecking contiguity ...\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e120a555-8b26-4273-9485-3edf045063ac",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92f90621-e7fc-4891-a5cd-69033c3c48e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#copy one of two above blocks and run again if needed (n/a for NC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "id": "cb60da52-ca13-45dd-8bf0-475213183a0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "underused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"overused units\")\n",
    "maxPlot = 1.06\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > maxPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"underused units\")\n",
    "minPlot = 0.94\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa912158-e8e9-46f3-8c3d-f6b17c26e62c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Note - for MA, above is second run-through after overuse, then underuse pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "id": "0d4f1372-6044-4803-91d9-de4b95a40083",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00013 1.00016 and their SDs are 0.11441 0.03978\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 4604\n",
      "working on HD 300 out of 4604\n",
      "working on HD 600 out of 4604\n",
      "working on HD 900 out of 4604\n",
      "working on HD 1200 out of 4604\n",
      "working on HD 1500 out of 4604\n",
      "working on HD 1800 out of 4604\n",
      "working on HD 2100 out of 4604\n",
      "working on HD 2400 out of 4604\n",
      "working on HD 2700 out of 4604\n",
      "working on HD 3000 out of 4604\n",
      "working on HD 3300 out of 4604\n",
      "working on HD 3600 out of 4604\n",
      "working on HD 3900 out of 4604\n",
      "working on HD 4200 out of 4604\n",
      "working on HD 4500 out of 4604\n",
      "all done checking HD and complement contiguity for all 4604 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs) \n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "id": "105ee28c-e042-4d8f-b825-4d55afaf6b7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets write these UNIT lists to a file\")   #DONE\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"VRApatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15ddb07a-3868-4633-8411-419749ac9451",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "id": "ecd50c96-51ce-4d83-b0df-e8c645c35815",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on full or partial VTD master list for unit 0\n",
      "working on full or partial VTD master list for unit 2000\n",
      "working on full or partial VTD master list for unit 4000\n",
      "Now converting unit lists to vtd lists for all HDs\n"
     ]
    }
   ],
   "source": [
    "#THIS WORKS FOR BOTH VTD- AND UNIT-BASED (FRAG VTD) -- **NOTE: DOES NOT ADD IN CUT DISTRICTS AND REBALANCE WEIGHTS\n",
    "print(\"after above patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))  #for simple states where units are at least whole vtd's\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist, unitFragVTDlist, unitVTDfrac = [list() for u in range(nUnits)], [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "unitFullVTDlist, unitPartialVTDlist =       [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "\n",
    "for u in range(nUnits):\n",
    "    if u %2000 == 0:\n",
    "        print(\"working on full or partial VTD master list for unit\",u)\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "        unitFullVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "            unitFullVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        if noFrag == 1:\n",
    "            unitVTDlist[u].append(allUnits[u] )\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitVTDlist[u].append(surroundedVTDs[i])\n",
    "        else:\n",
    "            unitFragVTDlist[u].append(allUnits[u])\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitFragVTDlist[u].append(surroundedVTDs[i])\n",
    "            vtdFrac = [0. for V in range(nVTDs)]\n",
    "            for vv in unitFragVTDlist[u]:\n",
    "                V = parentVTDno[vv]\n",
    "                if len(VTDchildren[V]) == 1:  #nonfragmented vtd\n",
    "                    vtdFrac[V] = 1.\n",
    "                else:\n",
    "                    if tractPop[V] > 0:\n",
    "                        vtdFrac[V] += fragVTDgeom[vv].area / vtdGeom[V].area #fragVTDpop[uu] / tractPop[v]  #we overwrote the frag pops earlier; can't use\n",
    "            for v in range(nVTDs):\n",
    "                if vtdFrac[v] > 0.0001:\n",
    "                    if vtdFrac[v] > 0.999:\n",
    "                        unitFullVTDlist[u].append(v)\n",
    "                    else:\n",
    "                        unitPartialVTDlist[u].append(v)\n",
    "                        unitVTDfrac[u].append(vtdFrac[v] )\n",
    "                                    \n",
    "HDpartialVTDlist, HDfullVTDlist, HDvtdFrac = [list() for t in range(nHDs)] ,[list() for t in range(nHDs)],[list() for t in range(nHDs)]               \n",
    "print(\"Now converting unit lists to vtd lists for all HDs\")\n",
    "if noFrag == 1:\n",
    "    for t in popHDlist:\n",
    "        for u in HDunitList[t]:\n",
    "            vtdList[t] += unitVTDlist[u]\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "else:\n",
    "    for t in popHDlist:\n",
    "        partialList, partialFrac = list(), list()  #for many HDs, we'll recover whole VTDs when aggregating units\n",
    "        for u in HDunitList[t]:\n",
    "            HDfullVTDlist[t] +=   unitFullVTDlist[u] \n",
    "            partialList +=         unitPartialVTDlist[u]\n",
    "            partialFrac +=          unitVTDfrac[u]\n",
    "        partialSet = set(partialList)  #non-duplicated set of partials across the HD, prepping to aggregate where possible\n",
    "        partialSetFrac, partialSetList = [0. for v in partialSet], list(partialSet)\n",
    "        for i,v in enumerate(partialList):\n",
    "            partialSetFrac[partialSetList.index(v)] += partialFrac[i]\n",
    "        for i,v in enumerate(partialSetList):\n",
    "            if partialSetFrac[i] > 0.999:  #the district has all the fragments of the original VTD contained in the HD's units\n",
    "                HDfullVTDlist[t].append(v)\n",
    "            else:\n",
    "                HDpartialVTDlist[t].append(v)\n",
    "                HDvtdFrac[t].append(      r5(partialSetFrac[i]) )  #save the aggregated fraction of this VTD across all units\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"VRApatchedVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "5075814f-4a75-4807-ad8d-b3cc969cb470",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4604 4604 4604 4604 4604 4604\n"
     ]
    }
   ],
   "source": [
    "\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDvPop = HDvPop[0:nHDs]\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDfullVTDlist = HDfullVTDlist[0:nHDs]\n",
    "HDpartialVTDlist = HDpartialVTDlist[0:nHDs]\n",
    "HDvtdFrac = HDvtdFrac[0:nHDs]\n",
    "hdCPx, hdCPy = hdCPx[0:nHDs], hdCPy[0:nHDs]\n",
    "print(nHDs,len(tList), len(HDweight), len(HDvPop), len(HDvtdFrac), len(hdCPx) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "id": "e385f357-5b7e-46f5-b054-c5c38d799395",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0 4604\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight), nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "8d922813-2854-41d7-9405-22db5d5d5a59",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now append the cut districts and adjust the HDweights\n",
      "8 0 are the number of HD-drawn and cut districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Now append the cut districts and adjust the HDweights\")\n",
    "print(nDistricts,nCutDistricts,\"are the number of HD-drawn and cut districts\")\n",
    "HDweight = [nDistricts/float(nCutDistricts + nDistricts) * HDweight[t] for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "if type(hdCPx) != type(list()):\n",
    "    hdCPx, hdCPy = hdCPx.to_list(), hdCPy.to_list()\n",
    "for L in allCutLists:\n",
    "    tList.append(len(tList))\n",
    "    HDweight.append(1./(nCutDistricts + nDistricts))\n",
    "    pop = np.sum([tractPop[v] for v in L])\n",
    "    HDvPop.append(pop )\n",
    "    HDfullVTDlist.append(L)\n",
    "    HDpartialVTDlist.append(list() )\n",
    "    HDvtdFrac.append(list() )\n",
    "    hdCPx.append(np.sum([tractPop[v]*tractCPx[v] for v in L]) / pop )\n",
    "    hdCPy.append(np.sum([tractPop[v]*tractCPy[v] for v in L]) / pop )\n",
    "    \n",
    "\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                        \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedWithCutsVTDs.csv\"   #patchDown, PatchUp, PatchBoth #patchedWithCutsVTDs #patchedVTDs\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "id": "b9d808de-119f-4197-8e0c-8407c105d789",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that VTDs are represented 1.0 across all units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"checking that VTDs are represented 1.0 across all units\")\n",
    "vtdUSE = [0. for v in range(nVTDs)]\n",
    "for u in range(nUnits):\n",
    "    for v in unitFullVTDlist[u]:\n",
    "        vtdUSE[v] += 1\n",
    "    for i,v in enumerate(unitPartialVTDlist[u]):\n",
    "        vtdUSE[v] += unitVTDfrac[u][i]\n",
    "plotVTDs, plotUses = list(), list()\n",
    "for v in range(nVTDs):\n",
    "    if tractPop[v] > 0  and v not in allCutVTDs:\n",
    "        plotVTDs.append(v)\n",
    "        plotUses.append(vtdUSE[v])\n",
    "plt.scatter(plotVTDs, plotUses)\n",
    "plt.show()\n",
    "for i,v in enumerate(plotVTDs):\n",
    "    if plotUses[i] > 0.1 and plotUses[i] < 0.9 :\n",
    "        print(v,tractPop[v], plotUses[i],\"vtd no, its pop, and usage across all units\")\n",
    "        plotPoly(tractGeom[v])\n",
    "unused = list()\n",
    "for v in range(nVTDs):\n",
    "    if vtdUSE[v] < 0.2 and MAP.contains(vtdGeom[v].centroid) and tractPop[v] > 0:\n",
    "        unused.append(v)\n",
    "        #print(v,\"in county\",countyNo[v],\"has pop\",tractPop[v],\"and map-total usage of\",vtdUSE[v],\"its surroundedness is\",v in surroundedVTDs)\n",
    "        plotPoly(vtdGeom[v].centroid.buffer(0.1))\n",
    "        plotCenter(v,vtdGeom[v],8)\n",
    "    #if vtdUSE[v] > 0.2 and vtdUSE[v] < 0.95:\n",
    "    #    plotCenter(r3(vtdUSE[v]),vtdGeom[v])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "id": "404935e6-f0de-4b51-9db9-020aa208f852",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "integrity check: vtd-based pops.  These should all be within single digits\n",
      "x = n surrounded, y= unit - vtd-based\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t, HDunit-based pop - pop from vtd-based HDs 585 -11.291\n",
      "t, HDunit-based pop - pop from vtd-based HDs 748 -11.279\n",
      "t, HDunit-based pop - pop from vtd-based HDs 1503 -11.298\n",
      "t, HDunit-based pop - pop from vtd-based HDs 1905 -11.793\n",
      "Here are the HD centers with significant pop difference between unit-based and vtd-based HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"integrity check: vtd-based pops.  These should all be within single digits\")\n",
    "HDvtdbasedPop = [0. for t in range(nHDs)]\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "nSurrs = [0. for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "        if u in surroundedVTDs:\n",
    "            nSurrs[t] += 1\n",
    "    for v in HDfullVTDlist[t]:\n",
    "        HDvtdbasedPop[t] += origVTDpop[v] #tractPop[v]\n",
    "    for i,v in enumerate(HDpartialVTDlist[t]):\n",
    "        HDvtdbasedPop[t] += HDvtdFrac[t][i] * origVTDpop[v] #tractPop[v] also works\n",
    "        \n",
    "plt.scatter([nSurrs[t] for t in popHDlist], [HDvPop[t] - HDvtdbasedPop[t] for t in popHDlist] )\n",
    "print(\"x = n surrounded, y= unit - vtd-based\")\n",
    "plt.show()\n",
    "plotThis = False\n",
    "for t in popHDlist:  #seems like for TN, we lost a vtd in converting from unit-based to vtd-based\n",
    "    if abs(HDvPop[t] - HDvtdbasedPop[t]) > 10:\n",
    "        plotThis = True\n",
    "        print(\"t, HDunit-based pop - pop from vtd-based HDs\",t,r3(HDvPop[t] - HDvtdbasedPop[t]) )\n",
    "        plotPoly(tractCP[t].buffer(0.1))\n",
    "if plotThis:\n",
    "    plotPoly(MAP)\n",
    "    print(\"Here are the HD centers with significant pop difference between unit-based and vtd-based HD lists\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef27af54-daf5-4e8f-9230-bce5b0b1e705",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "id": "3ad3342b-b8e3-46f5-a3e5-f49df386b88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\n",
      "Let's read in the 2020 and 2016 voting data for MO\n",
      "In year/election 2020 Dem and GOP total votes were 1253000 1718714 for a stateGOP of 0.57836\n",
      "There are a total of 4604  vote-mapped voting districts from election(s) in year  2020\n",
      "In year/election 2016 Dem and GOP total votes were 1071064 1594495 for a stateGOP of 0.59818\n",
      "There are a total of 4604  vote-mapped voting districts from election(s) in year  2016\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\")\n",
    "#note: we started w possibility of separate election --> 2020 vtd files by year.  Now we use ALARM combined 2016+2020 --> 2020 csv's for all exc CA\n",
    "# copied from \"HDpartisanAnalysis\"\n",
    "print(\"Let's read in the 2020 and 2016 voting data for\",STATE)\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G16PREDCLI\"], [\"G16PRERTRU\" ], list()\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G20PREDBID\", \"G16PREDCli\"], [\"G20PRERTRU\" ,\"G16PRERTru\" ], list()\n",
    "DemCandidates, RepCandidates, vestDFs = [\"pre_20_dem_bid\", \"pre_16_dem_cli\"], [\"pre_20_rep_tru\" ,\"pre_16_rep_tru\" ], list()\n",
    "nYears = 2\n",
    "unitIDs, vestReps,vestDems,yearLean = [list()]*nYears, [0]*nYears, [0]*nYears, [0.5]*nYears\n",
    "years = [str(2020),str(2016)]\n",
    "DemVotes, RepVotes = [list() for y in years], [list() for y in years]\n",
    "vestDir = \"./state_map_files/\" + STATE.lower()\n",
    "vestDF = pd.read_csv(vestDir + \"_2020_vtd.csv\")\n",
    "mergedDF = vestDF.copy() #pd.merge(mergedDF,vestDF, on = \"GEOID20\")\n",
    "for y,year in enumerate(years):\n",
    "    DemVotes[y], RepVotes[y], unitIDs[y] = mergedDF[DemCandidates[y]], mergedDF[RepCandidates[y]], vestDF[(\"GEOID20\")]\n",
    "    vestDems[y], vestReps[y] = np.sum(DemVotes[y]), np.sum(RepVotes[y])\n",
    "    yearLean[y] = vestReps[y]/float(vestDems[y]+vestReps[y])\n",
    "    print(\"In year/election\",year,\"Dem and GOP total votes were\",int(vestDems[y]),int(vestReps[y]),\"for a stateGOP of\",r5(yearLean[y]) )\n",
    "    nVTDs = len(DemVotes[y])\n",
    "    print(\"There are a total of\",nVTDs,\" vote-mapped voting districts from election(s) in year \",years[y])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f628069d-4177-401e-bf49-b7f194d0ef8b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "id": "5cf73783-4a48-4a3f-a2e3-c1b9ff32c859",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's read in our ensemble of HD districts for MO\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv MO4604VRApatchedVTDs.csv\n",
      "enter the number of Congr'l districts in the state; e.g. 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This ensemble or enacted map describes 4604 drawn districts.  This state has 8 districts per map\n",
      "converting vtd list strings to vtd lists by drawn district ...\n",
      "the total weight across all rows should be 1.000, actually is 1.0\n",
      "I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\n",
      "translating from HD order of precinct rows to VEST order\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's read in our ensemble of HD districts for\",STATE)\n",
    "infilename = input(\"enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv\")\n",
    "\n",
    "HDdf = pd.read_csv(\"2024state_HD_output/\"+infilename)\n",
    "nRows = len(HDdf)\n",
    "nStateDistricts = int(input(\"enter the number of Congr'l districts in the state; e.g. 8\"))\n",
    "print(\"This ensemble or enacted map describes\",nRows,\"drawn districts.  This state has\",nStateDistricts,\"districts per map\")\n",
    "\n",
    "HDvPop = HDdf[\"HDvPop\"].to_list()\n",
    "HDweight = HDdf['HDweight'].to_list()\n",
    "#tractPop = HDdf['tractPop'].to_list()\n",
    "#statePop = np.sum(tractPop)\n",
    "tractCPx = HDdf['centroid x'].to_list()\n",
    "tractCPy = HDdf['centroid y'].to_list()\n",
    "HDvtdListString = HDdf[\"HDvtdList\"]\n",
    "print(\"converting vtd list strings to vtd lists by drawn district ...\")\n",
    "HDvtdList = [list() for t in range(nRows) ]\n",
    "for t in range(nRows):\n",
    "    if HDvtdListString[t] != \"[]\":\n",
    "        HDvtdList[t] = ast.literal_eval(HDvtdListString[t])\n",
    "\n",
    "if \"partials\" in HDdf.columns.values: #\"splitTractNo\" #.to_list():\n",
    "    splitTractList, splitTractUseList = HDdf['partials'], HDdf['HDvtdFrac']\n",
    "    splitTractNo = [ast.literal_eval(splitTractList[t])    for t in range(nRows)]\n",
    "    splitTractUse = [ast.literal_eval(splitTractUseList[t]) for t in range(nRows)]\n",
    "else :  #incoming file didn't use any partial units, only whole ones\n",
    "    splitTractNo, splitTractUse = [[] for t in range(nRows)] , [ [] for t in range(nRows)]\n",
    "\n",
    "print(\"the total weight across all rows should be 1.000, actually is\",r5(np.sum(HDweight)) )\n",
    "print(\"I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\")\n",
    "censusGEOID20 = [ str( tractPopFile['GEOID20'][i]) for i in range(len(tractPopFile['GEOID20'])) ] #force strings to match\n",
    "miniHDdf = pd.DataFrame( {\"GEOID20\":censusGEOID20} )\n",
    "vestNo = [v for v in range(nVTDs)]\n",
    "print(\"translating from HD order of precinct rows to VEST order\")\n",
    "mergedGEO = [str(mergedDF['GEOID20'][i]) for i in range(len(mergedDF['GEOID20'])) ]  #force strings to match\n",
    "miniVestDF = pd.DataFrame( {\"GEOID20\":mergedGEO, \"vestNo\":vestNo} )\n",
    "mappingDF = pd.merge(miniHDdf,miniVestDF,on=\"GEOID20\")\n",
    "vestID = mappingDF['vestNo']  #this maps each named unit in a HDVL to the correct vestNo row with voting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "id": "540c6d1d-7728-48bf-90f0-f124b25ac7c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sanity check - Dem-leaning vtds for year 2020\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"sanity check - Dem-leaning vtds for year\",years[0])  #for MA, do GOP-leaning.  Other states, use Dem-leaning\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.2)\n",
    "    if DemVotes[0][vestID[v]] > RepVotes[0][vestID[v]]:\n",
    "        plt.text(vtdGeom[v].centroid.x, vtdGeom[v].centroid.y, \"D\", color = \"blue\",fontsize=6)\n",
    "        #plotCenter(\"d\",vtdGeom[v],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 409,
   "id": "56ed7e9d-1400-4848-892e-737555552d58",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\n",
      "working on drawn district no 0\n",
      "working on drawn district no 1000\n",
      "working on drawn district no 2000\n",
      "working on drawn district no 3000\n",
      "working on drawn district no 4000\n",
      "here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\n",
      "true 2020: 1253000 1718714 465713\n",
      "ensemble : 1254577 1717045 462467\n",
      "the true and ensemble state GOP leans are 0.57836 0.5778139244305862\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\")\n",
    "nDrawnDistricts = len(HDweight)  #now including cut districts\n",
    "nMapDistricts = nCutDistricts + nDistricts\n",
    "nEnsembleDems, nEnsembleReps = [0.]*nYears, [0.]*nYears\n",
    "y=0\n",
    "for t in range(nDrawnDistricts):\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on drawn district no\",t)\n",
    "    nEnsembleDems[y] += nMapDistricts* HDweight[t] * ( np.sum([DemVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([DemVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "    nEnsembleReps[y] += nMapDistricts* HDweight[t] * ( np.sum([RepVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([RepVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "\n",
    "print(\"here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\")\n",
    "print(\"true 2020:\",int(vestDems[y]),int(vestReps[y]),              int(vestReps[y] - vestDems[y]) )\n",
    "print(\"ensemble :\",int(nEnsembleDems[y]),int(nEnsembleReps[y]),    int(nEnsembleReps[y] - nEnsembleDems[y]) )\n",
    "print(\"the true and ensemble state GOP leans are\",r5(vestReps[y]/(vestReps[y]+vestDems[y])),\n",
    "      nEnsembleReps[y]/(nEnsembleReps[y]+nEnsembleDems[y]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 411,
   "id": "5c607c63-df0d-4334-8131-368c090c76d2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total drawn districts, HD-drawn, map districts 4604 4604 8\n"
     ]
    }
   ],
   "source": [
    "print(\"total drawn districts, HD-drawn, map districts\",nDrawnDistricts,nHDs, nMapDistricts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb0d0d12-6bf4-4d5f-9236-fa8735393e98",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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